{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "140f4d48",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import datetime\n",
    "import numpy as np\n",
    "import math\n",
    "from aqi import AQI\n",
    "import matplotlib.pyplot as plt\n",
    "import tensorflow as tf\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.utils import shuffle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "649d7d3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def exclude(x):\n",
    "    if 39.26<float(x[' lat'])<41.03 and 115.25<float(x[' lon'])<117.30:\n",
    "        return 'yes'\n",
    "'''\n",
    "市界的地理坐标为：北纬39\"26'至41\"03'，东经115\"25'至117\"30'。 北京市区坐标为：北纬39.9\"，东经116. 3\"。2018年3月29日\n",
    "'''\n",
    "\n",
    "def judge(dict_as):\n",
    "    dict_a = dict_as.copy()\n",
    "    dicts = {\n",
    "        'PM2.5': [None],\n",
    "        'PM10': [None],\n",
    "        'SO2': [None],\n",
    "        'NO2': [None],\n",
    "        'CO': [None],\n",
    "        'O3': [None],\n",
    "        'WIND': [None],\n",
    "        'TEMP': [None],\n",
    "        'RH': [None],\n",
    "        'PA': [None]\n",
    "    }\n",
    "    for j in dict_a:\n",
    "        for g in dicts:\n",
    "            if j == g:\n",
    "                dicts[g].append(dict_a[j])\n",
    "                break\n",
    "    # print(dicts)\n",
    "    # exit()\n",
    "    def_list = []\n",
    "    wind = {'0': [0, 0.2], '1': [0.3, 1.5], '2': [1.6, 3.3], '3': [3.4, 5.4], '4': [5.5, 7.9], '5': [8.0, 10.7],\n",
    "            '6': [10.8, 13.8], '7': [13.9, 17.1], '8': [17.2, 20.7], '9': [20.8, 24.4], '10': [24.5, 28.4],\n",
    "            '11': [28.5, 32.6], '12': [32.7, 36.9], '13': [37.0, 41.4], '14': [41.5, 46.1], '15': [46.2, 50.9],\n",
    "            '16': [51.0, 56.0], '17': [56.1, 1000]}\n",
    "    temp = {'极寒': [-1000, -40], '奇寒': [-39.9, -35], '酷寒': [-34.9, -30], '严寒': [-29.9, -20], '深寒': [-19.9, -15],\n",
    "            '大寒': [-14.9, -10], '小寒': [-9.9, -5],\n",
    "            '轻寒': [-4.9, 0], '微寒': [0, 4.9], '凉': [5, 9.9], '温凉': [10, 11.9],\n",
    "            '微温凉': [12, 13.9], '温和': [14, 15.9], '微温和': [16, 17.9], '温暖': [18, 19.9], '暖': [20, 21.9], '热': [22, 24.9],\n",
    "            '炎热': [25, 27.9], '暑热': [28, 29.9], '酷热': [30, 34.9], '奇热': [35, 39.9], '极热': [40, 1000]}\n",
    "    rh = {'特别重度干旱': [0, 29.9], '重度干旱': [30.0, 39.9], '中度干旱': [40.0, 49.9], '轻度干旱': [50.0, 59.9], '无旱': [60.0, 100.0]}\n",
    "    pa = {'低真空度': [10 ** 2, 10 ** 5 - 0.1], '正常气压': [10 ** 5, 10 ** 8]}\n",
    "    level_dict = {\n",
    "        \"PM2.5\": [0, 35, 75, 115, 150, 250, 10000],\n",
    "        \"PM10\": [0, 50, 150, 250, 350, 420, 10000],\n",
    "        \"SO2\": [0, 50, 150, 475, 800, 1600, 10000],\n",
    "        \"NO2\": [0, 40, 80, 180, 280, 565, 10000],\n",
    "        \"CO\": [0, 2, 4, 14, 24, 36, 10000],\n",
    "        \"O3\": [0, 160, 200, 300, 400, 800, 10000]  # 1小时浓度限值\n",
    "    }\n",
    "    pollution = [\"优\", \"良\", \"轻度污染\", \"中重污染\", \"重度污染\", \"严重污染\"]\n",
    "\n",
    "    def new_round(_float, _len):\n",
    "        '''\n",
    "        四舍五入\n",
    "        :param _float: 浮点数\n",
    "        :param _len:    保留的小数位\n",
    "        :return:\n",
    "        '''\n",
    "        if isinstance(_float, float):\n",
    "            if str(_float)[::-1].find('.') <= _len:\n",
    "                return (_float)\n",
    "            if str(_float)[-1] == '5':\n",
    "                return (round(float(str(_float)[:-1] + '6'), _len))\n",
    "            else:\n",
    "                return (round(_float, _len))\n",
    "        else:\n",
    "            return (round(_float, _len))\n",
    "\n",
    "    def where_6(name, list_c):\n",
    "        if len(dicts[name]) == 2:\n",
    "            x_a = dict_a[name]\n",
    "            for i in range(len(list_c) - 1):\n",
    "                if x_a < list_c[i + 1]:\n",
    "                    dict_a[name] = pollution[i]\n",
    "        else:\n",
    "            pass\n",
    "\n",
    "    def where_temp(name, list_d):\n",
    "        if len(dicts[name]) == 2:\n",
    "            x_b = dict_a[name]\n",
    "            x_b = new_round(x_b - 273.15, 1)\n",
    "            for i in list_d:\n",
    "                if list_d[i][0] <= x_b <= list_d[i][1]:\n",
    "                     dict_a[name] = i\n",
    "        else:\n",
    "            pass\n",
    "\n",
    "    def where_wind(name,list_d):\n",
    "        if len(dicts[name]) == 2:\n",
    "            x_b = dict_a[name]\n",
    "            x_b = new_round(x_b, 1)\n",
    "            for i in list_d:\n",
    "                if list_d[i][0] <= x_b <= list_d[i][1]:\n",
    "                    dict_a[name] = i\n",
    "\n",
    "    def where_rh(name,list_d):\n",
    "        if len(dicts[name]) == 2:\n",
    "            x_b = dict_a[name]\n",
    "            x_b = new_round(x_b, 1)\n",
    "            for i in list_d:\n",
    "                if list_d[i][0] <= x_b <= list_d[i][1]:\n",
    "                    dict_a[name] = i\n",
    "\n",
    "    def where_pa(name, list_d):\n",
    "        if len(dicts[name]) == 2:\n",
    "            x_b = dict_a[name]\n",
    "            x_b = new_round(x_b, 1)\n",
    "            for i in list_d:\n",
    "                if list_d[i][0] <= x_b <= list_d[i][1]:\n",
    "                    dict_a[name] = i\n",
    "\n",
    "    for i, j in enumerate(level_dict):\n",
    "        where_6(j, level_dict[j])\n",
    "    where_temp('TEMP', temp)\n",
    "    where_wind('WIND', wind)\n",
    "    where_rh('RH', rh)\n",
    "    where_pa('PA', pa)\n",
    "    return dict_a\n",
    "\n",
    "def wind(data):\n",
    "    x = float(data[' U(m/s)'])\n",
    "    y = float(data[' V(m/s)'])\n",
    "    return math.sqrt(x*x+y*y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "0180ec2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_pd(path):\n",
    "#     path = r'D:\\污染\\2017'\n",
    "    path_all = list(os.walk(path))[0][2]\n",
    "    all_path = []\n",
    "    for i in path_all:\n",
    "        all_path.append(path + '\\\\' + i)\n",
    "    pd_all = []\n",
    "    for i in range(len(path_all)):\n",
    "        time_info = path_all[i].split('ysis')[1].split('.')[0]\n",
    "        y = int(time_info[0:4])\n",
    "        m = int(time_info[4:6])\n",
    "        d = int(time_info[6:8])\n",
    "        h = int(time_info[8:10])\n",
    "        print(time_info, y, m, d, h)\n",
    "        data = pd.read_csv(all_path[i])\n",
    "        data['time'] = datetime.datetime(year=y, month=m, day=d, hour=h)\n",
    "        data.index =data['time']\n",
    "        data.drop('time', axis=1, inplace=True)\n",
    "        data['judge'] = data.apply(exclude, axis=1)\n",
    "        data = data[data['judge'] == 'yes']\n",
    "        pd_all.append(data)\n",
    "    DataAll = pd.concat(pd_all)\n",
    "    DataAll['wind'] = DataAll.apply(wind, axis=1)\n",
    "    DataAll.drop([' ','judge',' U(m/s)',' V(m/s)',' lat',' lon'],axis=1, inplace=True)\n",
    "    DataAll.columns = ['PM2.5', 'PM10', 'SO2', 'NO2', 'CO', 'O3', 'TEMP', 'RH', 'PA', 'WIND']\n",
    "    data_list2 = []  # max(list(AQI(list(DataAll.iloc[i].to_dict().values())[0:6]).get_IAQ(hour=True).values()))\n",
    "    for i in range(DataAll.shape[0]):\n",
    "        data_list2.append(max(list(AQI(list(DataAll.iloc[i].to_dict().values())[0:6]).get_IAQ(hour=True).values())))\n",
    "        #     data_list.append(list(judge(DataAll.iloc[i].to_dict()).values())\n",
    "    DataAll['aqi'] =  data_list2\n",
    "    return DataAll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1955ac43",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PM2.5</th>\n",
       "      <th>PM10</th>\n",
       "      <th>SO2</th>\n",
       "      <th>NO2</th>\n",
       "      <th>CO</th>\n",
       "      <th>O3</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>RH</th>\n",
       "      <th>PA</th>\n",
       "      <th>WIND</th>\n",
       "      <th>aqi</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>296.60</td>\n",
       "      <td>295.60</td>\n",
       "      <td>23.13</td>\n",
       "      <td>100.73</td>\n",
       "      <td>3.44</td>\n",
       "      <td>6.50</td>\n",
       "      <td>273.76</td>\n",
       "      <td>39.15</td>\n",
       "      <td>100369.12</td>\n",
       "      <td>1.352036</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>472.55</td>\n",
       "      <td>465.82</td>\n",
       "      <td>27.29</td>\n",
       "      <td>116.78</td>\n",
       "      <td>5.61</td>\n",
       "      <td>5.39</td>\n",
       "      <td>273.35</td>\n",
       "      <td>41.42</td>\n",
       "      <td>101946.08</td>\n",
       "      <td>0.358469</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>492.42</td>\n",
       "      <td>482.45</td>\n",
       "      <td>31.50</td>\n",
       "      <td>119.89</td>\n",
       "      <td>6.11</td>\n",
       "      <td>5.19</td>\n",
       "      <td>272.77</td>\n",
       "      <td>43.60</td>\n",
       "      <td>102247.25</td>\n",
       "      <td>2.434831</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>464.30</td>\n",
       "      <td>460.67</td>\n",
       "      <td>31.82</td>\n",
       "      <td>114.53</td>\n",
       "      <td>5.91</td>\n",
       "      <td>4.79</td>\n",
       "      <td>272.29</td>\n",
       "      <td>45.32</td>\n",
       "      <td>102274.90</td>\n",
       "      <td>3.586879</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>430.77</td>\n",
       "      <td>433.55</td>\n",
       "      <td>31.06</td>\n",
       "      <td>111.65</td>\n",
       "      <td>5.66</td>\n",
       "      <td>4.68</td>\n",
       "      <td>271.90</td>\n",
       "      <td>47.59</td>\n",
       "      <td>102408.89</td>\n",
       "      <td>3.570658</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>8.06</td>\n",
       "      <td>12.01</td>\n",
       "      <td>2.57</td>\n",
       "      <td>5.52</td>\n",
       "      <td>0.25</td>\n",
       "      <td>58.22</td>\n",
       "      <td>265.15</td>\n",
       "      <td>39.45</td>\n",
       "      <td>97035.02</td>\n",
       "      <td>7.175974</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>9.16</td>\n",
       "      <td>14.62</td>\n",
       "      <td>2.73</td>\n",
       "      <td>6.52</td>\n",
       "      <td>0.27</td>\n",
       "      <td>58.20</td>\n",
       "      <td>265.24</td>\n",
       "      <td>40.49</td>\n",
       "      <td>97197.85</td>\n",
       "      <td>7.411511</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>7.31</td>\n",
       "      <td>10.59</td>\n",
       "      <td>2.51</td>\n",
       "      <td>5.64</td>\n",
       "      <td>0.25</td>\n",
       "      <td>58.48</td>\n",
       "      <td>263.93</td>\n",
       "      <td>41.01</td>\n",
       "      <td>95287.30</td>\n",
       "      <td>6.485985</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>7.37</td>\n",
       "      <td>10.97</td>\n",
       "      <td>2.44</td>\n",
       "      <td>5.17</td>\n",
       "      <td>0.25</td>\n",
       "      <td>58.35</td>\n",
       "      <td>263.98</td>\n",
       "      <td>42.61</td>\n",
       "      <td>95685.62</td>\n",
       "      <td>6.956048</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>7.65</td>\n",
       "      <td>11.77</td>\n",
       "      <td>2.46</td>\n",
       "      <td>5.37</td>\n",
       "      <td>0.25</td>\n",
       "      <td>57.79</td>\n",
       "      <td>263.54</td>\n",
       "      <td>43.27</td>\n",
       "      <td>95104.91</td>\n",
       "      <td>7.368372</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>112344 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      PM2.5    PM10    SO2     NO2    CO     O3    TEMP  \\\n",
       "time                                                                      \n",
       "2017-01-01 00:00:00  296.60  295.60  23.13  100.73  3.44   6.50  273.76   \n",
       "2017-01-01 00:00:00  472.55  465.82  27.29  116.78  5.61   5.39  273.35   \n",
       "2017-01-01 00:00:00  492.42  482.45  31.50  119.89  6.11   5.19  272.77   \n",
       "2017-01-01 00:00:00  464.30  460.67  31.82  114.53  5.91   4.79  272.29   \n",
       "2017-01-01 00:00:00  430.77  433.55  31.06  111.65  5.66   4.68  271.90   \n",
       "...                     ...     ...    ...     ...   ...    ...     ...   \n",
       "2017-01-31 23:00:00    8.06   12.01   2.57    5.52  0.25  58.22  265.15   \n",
       "2017-01-31 23:00:00    9.16   14.62   2.73    6.52  0.27  58.20  265.24   \n",
       "2017-01-31 23:00:00    7.31   10.59   2.51    5.64  0.25  58.48  263.93   \n",
       "2017-01-31 23:00:00    7.37   10.97   2.44    5.17  0.25  58.35  263.98   \n",
       "2017-01-31 23:00:00    7.65   11.77   2.46    5.37  0.25  57.79  263.54   \n",
       "\n",
       "                        RH         PA      WIND  aqi  \n",
       "time                                                  \n",
       "2017-01-01 00:00:00  39.15  100369.12  1.352036   50  \n",
       "2017-01-01 00:00:00  41.42  101946.08  0.358469   58  \n",
       "2017-01-01 00:00:00  43.60  102247.25  2.434831   61  \n",
       "2017-01-01 00:00:00  45.32  102274.90  3.586879   59  \n",
       "2017-01-01 00:00:00  47.59  102408.89  3.570658   57  \n",
       "...                    ...        ...       ...  ...  \n",
       "2017-01-31 23:00:00  39.45   97035.02  7.175974   18  \n",
       "2017-01-31 23:00:00  40.49   97197.85  7.411511   18  \n",
       "2017-01-31 23:00:00  41.01   95287.30  6.485985   18  \n",
       "2017-01-31 23:00:00  42.61   95685.62  6.956048   18  \n",
       "2017-01-31 23:00:00  43.27   95104.91  7.368372   18  \n",
       "\n",
       "[112344 rows x 11 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DataAll = pd.read_csv('./data.csv')\n",
    "DataAll.index = DataAll['time']\n",
    "DataAll.drop('time', axis =1,  inplace = True)\n",
    "DataAll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e56460c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>PA</th>\n",
       "      <th>WIND</th>\n",
       "      <th>aqi</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>296.60</td>\n",
       "      <td>273.76</td>\n",
       "      <td>39.15</td>\n",
       "      <td>100369.12</td>\n",
       "      <td>1.352036</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>472.55</td>\n",
       "      <td>273.35</td>\n",
       "      <td>41.42</td>\n",
       "      <td>101946.08</td>\n",
       "      <td>0.358469</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>492.42</td>\n",
       "      <td>272.77</td>\n",
       "      <td>43.60</td>\n",
       "      <td>102247.25</td>\n",
       "      <td>2.434831</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>464.30</td>\n",
       "      <td>272.29</td>\n",
       "      <td>45.32</td>\n",
       "      <td>102274.90</td>\n",
       "      <td>3.586879</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01 00:00:00</th>\n",
       "      <td>430.77</td>\n",
       "      <td>271.90</td>\n",
       "      <td>47.59</td>\n",
       "      <td>102408.89</td>\n",
       "      <td>3.570658</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>8.06</td>\n",
       "      <td>265.15</td>\n",
       "      <td>39.45</td>\n",
       "      <td>97035.02</td>\n",
       "      <td>7.175974</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>9.16</td>\n",
       "      <td>265.24</td>\n",
       "      <td>40.49</td>\n",
       "      <td>97197.85</td>\n",
       "      <td>7.411511</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>7.31</td>\n",
       "      <td>263.93</td>\n",
       "      <td>41.01</td>\n",
       "      <td>95287.30</td>\n",
       "      <td>6.485985</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>7.37</td>\n",
       "      <td>263.98</td>\n",
       "      <td>42.61</td>\n",
       "      <td>95685.62</td>\n",
       "      <td>6.956048</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31 23:00:00</th>\n",
       "      <td>7.65</td>\n",
       "      <td>263.54</td>\n",
       "      <td>43.27</td>\n",
       "      <td>95104.91</td>\n",
       "      <td>7.368372</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>112344 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      PM2.5    TEMP     RH         PA      WIND  aqi\n",
       "time                                                                \n",
       "2017-01-01 00:00:00  296.60  273.76  39.15  100369.12  1.352036   50\n",
       "2017-01-01 00:00:00  472.55  273.35  41.42  101946.08  0.358469   58\n",
       "2017-01-01 00:00:00  492.42  272.77  43.60  102247.25  2.434831   61\n",
       "2017-01-01 00:00:00  464.30  272.29  45.32  102274.90  3.586879   59\n",
       "2017-01-01 00:00:00  430.77  271.90  47.59  102408.89  3.570658   57\n",
       "...                     ...     ...    ...        ...       ...  ...\n",
       "2017-01-31 23:00:00    8.06  265.15  39.45   97035.02  7.175974   18\n",
       "2017-01-31 23:00:00    9.16  265.24  40.49   97197.85  7.411511   18\n",
       "2017-01-31 23:00:00    7.31  263.93  41.01   95287.30  6.485985   18\n",
       "2017-01-31 23:00:00    7.37  263.98  42.61   95685.62  6.956048   18\n",
       "2017-01-31 23:00:00    7.65  263.54  43.27   95104.91  7.368372   18\n",
       "\n",
       "[112344 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DataAll = DataAll[['PM2.5','TEMP', 'RH', 'PA', 'WIND','aqi']]\n",
    "DataAll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98c32f19",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82d58fc4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 离散特征\n",
    "data_list = []\n",
    "for i in range(DataAll.shape[0]):\n",
    "    data_list.append(list(judge(DataAll.iloc[i].to_dict()).values()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e3d9d65",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "da0f588b",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = DataAll[DataAll.columns[0:-1]].values\n",
    "features = np.reshape(features,(112344,5,1))\n",
    "labels = DataAll[DataAll.columns[-1]]\n",
    "\n",
    "train_x,test_x,train_y,test_y = train_test_split(features,labels,test_size=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "704ee821",
   "metadata": {},
   "outputs": [],
   "source": [
    "mean = train_x.mean(axis=0)\n",
    "std = train_x.std(axis=0)\n",
    "train_x = (train_x - mean) / std\n",
    "test_x =(test_x - mean) / std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae095ba6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7ea6dc5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44acff5e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a7a5dd55",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1bb9618",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ce2b777",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "23470301",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ddf93b5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "9e507488",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[          省名                   经度范围                 纬度范围\n",
       " 0        安徽省  114.878463~119.645188   29.395191~34.65234\n",
       " 1    澳门特别行政区  113.528164~113.598861  22.109142~22.217034\n",
       " 2        北京市  115.416827~117.508251  39.442078~41.058964\n",
       " 3        福建省   115.84634~120.722095  23.500683~28.317231\n",
       " 4        甘肃省   92.337827~108.709007  32.596328~42.794532\n",
       " 5        广东省  109.664816~117.303484  20.223273~25.519951\n",
       " 6    广西壮族自治区   104.446538~112.05675  20.902306~26.388528\n",
       " 7        贵州省  103.599417~109.556069  24.620914~29.224344\n",
       " 8        海南省  108.614575~117.842823     8.30204~20.16146\n",
       " 9        河北省   113.454863~119.84879  36.048718~42.615453\n",
       " 10       河南省   110.35571~116.644831    31.3844~36.366508\n",
       " 11      黑龙江省  121.183134~135.088511  43.422993~53.560901\n",
       " 12       湖北省  108.362545~116.132865  29.032769~33.272876\n",
       " 13       湖南省  108.786106~114.256514    24.643089~30.1287\n",
       " 14       吉林省  121.638964~131.309886  40.864207~46.302152\n",
       " 15       江苏省  116.355183~121.927472   30.76028~35.127197\n",
       " 16       江西省    89.551219~124.57284   8.972204~40.256391\n",
       " 17       辽宁省  118.839668~125.785614   38.72154~43.488548\n",
       " 18    内蒙古自治区    97.17172~126.065581  37.406647~53.333779\n",
       " 19   宁夏回族自治区  104.284332~107.661713  35.238497~39.387783\n",
       " 20       青海省   89.401764~103.068897  31.600668~39.212599\n",
       " 21       山东省  114.810126~122.705605  34.377357~38.399928\n",
       " 22       山西省   110.230241~114.56294  34.583784~40.744953\n",
       " 23       陕西省  105.488313~111.241907  31.706862~39.582532\n",
       " 24       上海市  120.852326~122.118227  30.691701~31.874634\n",
       " 25       四川省    97.347493~108.54257  26.048207~34.315239\n",
       " 26       台湾省  119.314417~123.701571  21.896939~25.938831\n",
       " 27       天津市  116.702073~118.059209  38.554824~40.251765\n",
       " 28     西藏自治区    78.386053~99.115351  26.853453~36.484529\n",
       " 29   香港特别行政区  113.815684~114.499703  22.134935~22.566546\n",
       " 30  新疆维吾尔自治区    73.501142~96.384783  34.336146~49.183097\n",
       " 31       云南省   97.527278~106.196958  21.142312~29.225286\n",
       " 32       浙江省  118.022574~122.834203  26.643625~31.182556\n",
       " 33       重庆市  105.289838~110.195637  28.164706~32.204171,\n",
       "             市名                   经度范围                 纬度范围\n",
       " 0    阿坝藏族羌族自治州  100.525204~104.434109   30.59529~34.315239\n",
       " 1        阿克苏地区    78.024406~84.084657  39.463565~42.647053\n",
       " 2         阿拉尔市     80.589897~81.97584  40.355693~40.943376\n",
       " 3         阿拉善盟     97.17172~106.86202  37.406647~42.794532\n",
       " 4        阿勒泰地区    85.526535~91.073824   45.00035~49.183097\n",
       " ..         ...                    ...                  ...\n",
       " 366       驻马店市  113.089976~115.207367  32.279965~33.534031\n",
       " 367        资阳市  104.433085~105.752797  29.675937~30.633443\n",
       " 368        淄博市  117.545151~118.516577   35.925714~37.28206\n",
       " 369        自贡市  104.050439~105.268801  28.926571~29.640196\n",
       " 370        遵义市  105.605788~108.210799  27.138909~29.224344\n",
       " \n",
       " [371 rows x 3 columns]]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_html('https://blog.csdn.net/esa72ya/article/details/114642127')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bf9de010",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3eae4086",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = tf.keras.Sequential()\n",
    "model.add(tf.keras.layers.LSTM(32, input_shape=(train_x.shape[1:]), return_sequences=True))\n",
    "model.add(tf.keras.layers.LSTM(32, return_sequences=True))\n",
    "model.add(tf.keras.layers.LSTM(32))\n",
    "model.add(tf.keras.layers.Dense(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5b57d7c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "790/790 [==============================] - 13s 11ms/step - loss: 3.8599 - val_loss: 3.9669\n",
      "Epoch 2/50\n",
      "790/790 [==============================] - 7s 9ms/step - loss: 3.8553 - val_loss: 3.9699\n",
      "Epoch 3/50\n",
      "790/790 [==============================] - 7s 9ms/step - loss: 3.8501 - val_loss: 3.9360\n",
      "Epoch 4/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.8402 - val_loss: 3.9116\n",
      "Epoch 5/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.8310 - val_loss: 3.9217\n",
      "Epoch 6/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.8246 - val_loss: 3.9014\n",
      "Epoch 7/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.8207 - val_loss: 3.9256\n",
      "Epoch 8/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.8047 - val_loss: 3.8970\n",
      "Epoch 9/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.8002 - val_loss: 3.8717\n",
      "Epoch 10/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7941 - val_loss: 3.8783\n",
      "Epoch 11/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7848 - val_loss: 3.8607\n",
      "Epoch 12/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7783 - val_loss: 3.8719\n",
      "Epoch 13/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7748 - val_loss: 3.8715\n",
      "Epoch 14/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7642 - val_loss: 3.8711\n",
      "Epoch 15/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7545 - val_loss: 3.8618\n",
      "Epoch 16/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7511 - val_loss: 3.8280\n",
      "Epoch 17/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7442 - val_loss: 3.8513\n",
      "Epoch 18/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7337 - val_loss: 3.8150\n",
      "Epoch 19/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7301 - val_loss: 3.8449\n",
      "Epoch 20/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7202 - val_loss: 3.8093\n",
      "Epoch 21/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7149 - val_loss: 3.8342\n",
      "Epoch 22/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7074 - val_loss: 3.8163\n",
      "Epoch 23/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.7011 - val_loss: 3.8279\n",
      "Epoch 24/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6931 - val_loss: 3.8011\n",
      "Epoch 25/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6855 - val_loss: 3.8431\n",
      "Epoch 26/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6780 - val_loss: 3.7991\n",
      "Epoch 27/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6759 - val_loss: 3.7847\n",
      "Epoch 28/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6663 - val_loss: 3.7755\n",
      "Epoch 29/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6611 - val_loss: 3.7738\n",
      "Epoch 30/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6531 - val_loss: 3.7925\n",
      "Epoch 31/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6533 - val_loss: 3.7705\n",
      "Epoch 32/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6454 - val_loss: 3.7553\n",
      "Epoch 33/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6387 - val_loss: 3.7604\n",
      "Epoch 34/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6328 - val_loss: 3.7682\n",
      "Epoch 35/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6236 - val_loss: 3.7390\n",
      "Epoch 36/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6205 - val_loss: 3.7834\n",
      "Epoch 37/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6179 - val_loss: 3.7373\n",
      "Epoch 38/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6096 - val_loss: 3.7489\n",
      "Epoch 39/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.6053 - val_loss: 3.7287\n",
      "Epoch 40/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5927 - val_loss: 3.7495\n",
      "Epoch 41/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5908 - val_loss: 3.7331\n",
      "Epoch 42/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5865 - val_loss: 3.7225\n",
      "Epoch 43/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5813 - val_loss: 3.6964\n",
      "Epoch 44/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5729 - val_loss: 3.7511\n",
      "Epoch 45/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5697 - val_loss: 3.7219\n",
      "Epoch 46/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5659 - val_loss: 3.6973\n",
      "Epoch 47/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5597 - val_loss: 3.7234\n",
      "Epoch 48/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5486 - val_loss: 3.7449\n",
      "Epoch 49/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5476 - val_loss: 3.6795\n",
      "Epoch 50/50\n",
      "790/790 [==============================] - 8s 10ms/step - loss: 3.5441 - val_loss: 3.7104\n"
     ]
    }
   ],
   "source": [
    "model.compile(optimizer=tf.keras.optimizers.Adam(), loss='mae')\n",
    "learning_rate_reduction = tf.keras.callbacks.ReduceLROnPlateau(monitor='val_loss', patience=3, factor=0.5, min_lr=0.001)\n",
    "history = model.fit(train_x, train_y,\n",
    "                    batch_size = 128,\n",
    "                    epochs=50,\n",
    "                    validation_data=(test_x, test_y),\n",
    "                    callbacks=[learning_rate_reduction])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f46a4ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "   # 当loss下降，val_loss下降：训练正常，最好情况。\n",
    "   # 当loss下降，val_loss稳定：网络过拟合化。这时候可以添加Dropout和Max pooling。\n",
    "  # 当loss稳定，val_loss下降：说明数据集有严重问题，可以查看标签文件是否有注释错误，或者是数据集质量太差。建议重新选择。\n",
    "  # 当loss稳定，val_loss稳定：学习过程遇到瓶颈，需要减小学习率（自适应网络效果不大）或batch数量。\n",
    "  # 当loss上升，val_loss上升：网络结构设计问题，训练超参数设置不当，数据集需要清洗等问题，最差情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f8f63cd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2248a16dc70>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.epoch, history.history.get('loss'), 'y', label='Training loss')\n",
    "plt.plot(history.epoch, history.history.get('val_loss'), 'b', label='Test loss')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e382fce3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "352/352 [==============================] - 1s 4ms/step - loss: 3.7104\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "3.7103610038757324"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 评估模型,不输出预测结果\n",
    "# loss,accuracy = \n",
    "model.evaluate(test_x,test_y)\n",
    "# print('\\ntest loss',loss)\n",
    "# print('accuracy',accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "dda9f113",
   "metadata": {},
   "outputs": [],
   "source": [
    "pre = model.predict(test_x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c2e4364e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# 支持中文\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "308a9ff0",
   "metadata": {},
   "outputs": [],
   "source": [
    "DataAll.to_csv('./data2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bb7e7d8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '2017一月份北京市关于pm2.5对于AQI数据的预测')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EOUqoDDJCREREHieE2A5KwuIKKeWMlHljoTSDeSZh2PX4vHIoF78joSQ5pgtlNK2LADwe7ysotuz28RG+Yq+Lj+I1AEoTGgFlBKZrY6OI3QDgKyllgxDiZSjJsCeklO/FyiiA0lwq3vF16nt6Gsow8A+rzP8eSi2QR6SUk1LmdYHSHOswAKdJKZsT5gVjcVYDuFRKuShN2b0AIHU0NbvFmi3NkVIuTDPvbgCPAnhHSvm/NPOPgJKwmg7gLDPN94QQx6d+pinzO0NJ3g0F0Cf2fT8KZej4f0sp1wshrgRwFZRtMhqbvy+UJlfXQvl+VgOYGyu2CEoC8+L4+5VS9os9PhFAiZRyXSzJ9WDsvb4XHxVOCDEVSpLzTCh9/3wAJaF1d2wbPAtAPyjJxyNj6xwPJZF1p1SGhN8HwPUAXoaSnBsmpbzR6OdIRETkVUwAERER+ZgQoih+MZwyPZCpTxqty5iMbVcow5WXZ11Ye5nFCUObW8qtBFAmseZiLX025QIhRLssNavMlH1ganJPCLFz4shksWkFiQnChOntY6OyERER5RwmgIiIiIiIiIiIchz7ACIiIiIiIiIiynFMABERERERERER5TgmgIiIiIiIiIiIclzIjZXutNNOslu3bm6smoiIiIiIiIgoJ02fPn2zlHLndPNcSQB169YN06ZNc2PVREREREREREQ5SQixSm0em4AREREREREREeU4JoCIiIiIiIiIiHIcE0BERERERERERDnOlT6AiIiIiIiIiIjs1NzcjNLSUjQ0NLgdiuWKi4vRtWtXFBQUaH4NE0BERERERERElHNKS0vRoUMHdOvWDUIIt8OxjJQS5eXlKC0tRffu3TW/jk3AiIiIiIiIiCjnNDQ0YMcdd8yp5A8ACCGw44476q7ZxAQQEREREREREeWkXEv+xBl5X0wAERERERERERE5oLm5GdFotOV5OBxGNBpFTU2N6mtWrFiBiooK0+tmAoiIiIiIiIiIyAbjxo3DOeecg4svvhi77747PvjgA/z5z3/GjjvuiEsvvRSXXnopJk6ciLPPPhtjxozBFVdcgRtvvBFXXXUVZs6cCQD48MMPWx6bwU6giYiIiIiIiIhscMopp+DBBx/E8OHDcfPNN+Oyyy7D7bffjnPPPRc//PBDy3JDhw5FRUUFgsEgnn32WXz++efYvHkz/u///g8nnngiAgHz9XdYA4iIiIiIiIiIyCbt27fH5MmTcdlll2HSpEk49thjsddee+H222/HYYcdhkmTJmHChAnYd999AQC33347KisrUVBQgMLCQsviYA0gIiIiIiIiIspp/xs8HwvWVVta5sFdtsOTFx+ScZnPP/8c/fv3h5QSp59+Os477zxccMEF2HbbbXHCCSegtLQUhxxyCB577DEceOCBAIBgMIjtttvO0lgB1gAiIiIiIiIiIrLFNddcgzFjxqBTp0449thj0aVLFwDAhg0bsNNOOwEAOnTogMGDB6N79+6QUqK5uRmhUAhSSktjYQ0gIiIiIiIiIspp2Wrq2CWx757nn38eM2bMwIoVK7BmzRrsueeeLUmeH3/8EUuWLEEoFEJ1dTU6dOjQkgyyLBbLSiIiIiIiIiIiorSCwSDat2+PvfbaC5s2bUJRURFOOOEERKNR9O3bF7fccguuvfZaHHDAAVi5ciVOP/10/Pe//7Vs/UwAERERERERERHZRErZUtPnkEMOQU1NDc466yxcf/31OOuss/D+++/jxBNPRIcOHfDEE0+gV69eKC4uxjvvvIMDDjgAixYtQjAYNB0Hm4AREREREREREdmgqakJJ554Iq655hqEw2HcfffdkFLirbfeQn19Pa688kr06tULV155JcrKyvDkk0+ia9eueOSRR7B+/Xps3LgRRx11FI499ljTsQirOxXSokePHnLatGmOr5dIt14dgaNuAC7p63YkREREREREpMPChQtx0EEHuR1GkrVr12L33XdveV5XV4eioiJDNXzSvT8hxHQpZY90y7MJGFE2Mz5xOwIiIiIiIiLKAYnJHwBo3769Jc27tGACiIiIiIiIiIgoxzEBRERERERERESU45gAIiIiIiIiIiJyQSQSgVN9M3MUMCIiIiIiIiIim3zwwQd4+eWXW/r/aWhoQHFxMQAlAfTtt99ihx12aFn+9ddfxzbbbINbbrnF0jiYACIiIiIiIiIiskkwGMS///1v3H777QCA4447DuPGjYMQomWZ2267DYsWLYIQAuvWrUMgEMCAAQMgpcRhhx2GN954w3QcTAAREREREREREdnsP//5DyZNmoTKykqcccYZaGxsxBVXXIH77rsPffv2xaeffoorr7wSX3zxBYqLi3HGGWdg8ODBuPXWWy1ZPxNAlDvqtgB9jwCu+x7oenTmZcNNyrLnvwQcdFH2sp/fA7h7KtBhVysiJSIiIiIiIicNewjYMNfaMnc9FDj/Bc2LV1ZW4m9/+xs6d+4MAJg5cyaqq6sBAEVFRTjooIPQp08f7LbbbgCAF154AbfddhsKCwstCZcJIModJeOAhipgwqvAVQMyL1tbBlSvBYY9oC0B1FgNLP0FOOpv1sRKREREREREeSEcDqOgoABSSuywww7YaaedAADbbbcdampqMGrUKDz55JMoKipCc3Mzli1bBiEE9ttvP/znP/9Bc3MzHn74YZx33nmm4mACiHJGUySKQgB1TRG0dzsYIiIiIiIi8g4dNXWstmHDBhxyyCHYb7/98M4772Dt2rUIBALYbbfdcM011+DMM8/EmWeeCQC46aabsNtuu6G8vByHH344Xn75ZcviYAKIcsa8tVU4CsCiDTU4yu1giIiIiIiIiADMnj0bV1xxBQ477DAceeSRWLlyJYqLiyGEwFVXXQVAGQ3snnvuQffu3dG5c2cUFxdjxowZuO666/Daa6+11BoyI2C6BCI3bV4GvHcm0FCFvZd8qL7ct7cAc79xLi4iIiIiIiLKe1u3bsXixYuxzTbb4KabbkKXLl0QjUYBAB06dMBll12G2bNn4/jjj0enTp3wxBNPQEoJAOjbty8OPPBA7Lfffvj9999Nx8IaQORvY54D1k4Hlo5Epy2z1Zeb+7Xy79C/OhcbERERERER5bWxY8eiZ8+emDt3Lvr164eamhq8/PLLGDBgAE488UR06tQJ3bp1wwsvvICzzjoLAFBXV4dgMAgAeOyxx9CzZ090797ddCxMABERERERERER2eCCCy7ABRdckDRtxYoVLY/jff/Ekz8AcP/99yctv/fee1sSC5uAERERERERERHlOCaAyNsWDwPGv5Z9uXBjy0MBqb7cD3cBvToCs77QH8uoZ4CS8fpfR0RERERERK6I96eTa4y8LyaAyNu+uBr49cnsyy39RVt5swYof0c/E5sgtMeydSPw8YXalyciIiIiIiLXFBcXo7y8POeSQFJKlJeXo7i4WNfr2AcQEREREREREeWcrl27orS0FJs2bXI7FMsVFxeja9euul6jKQEkhNgFwDdSylOEEAUAvgewA4D3pZQfppumL3QiIiIiIiIiIusUFBRYMnpWrsjaBEwIsT2ATwBsE5v0TwDTpJQnArhICNFBZRrlkqZaYPjDQFOd8TJqNgIjnwCiEeviionkVo0+IiIiIiIiIktp6QMoAuAqANWx56cDGBR7PBFAD5VpSYQQtwohpgkhpuVi9aucN7EfMOkt5Z9RP/0TmPA6UDLOurhiymoaLC+TiIiIiIiIKFdkTQBJKaullFUJk7YBsDb2uBrALirTUsvpL6XsIaXssfPOO5uLmpwXbVb+yqjxMiKxkbpsqAFEREREREREROqMjAK2FUC72ONtY2Wkm0aUQseIWybKzrEO3omIiIiIiIhMM5KomQ7g5NjjwwGUqEyjXBLPqsz63IrCLChDXVlNI1aXa+yrSKQkpSrXAFPesz4oIiIiIiIiIhcZGQb+EwBDhRCnADgYwGQozb9Sp1Euqigx/trUZIsVVKr7LNlYgz13bK//9QP+AmxeAhxyGbDNThYESEREREREROQ+zTWApJSnx/6uAnAOgAkAzpZSRtJNsyFWyhVebqJVX6H8NdPXEREREREREZHHGKkBBCnlOrSO+qU6jSiZDTWA7KhVRERERERERJRj2FkzaWRltR0HqwBtWQksHqZt2aW/ArWbtJc9ZxBQW24sLiIiIiIiIiIHGaoBRGRIvLaOk8N09TumdQj7bD6/POFJlppFlWuA7/4B7HUycNMQw+EREREREREROYE1gMhBLjTX0pr80SvSpPytWWdP+UREREREREQWYgKI/C1WmygxtST0NDFjH0JERERERESUB9gEjHKCtDqRU7Me+OONDCv08lBmRERERERERMmYACIX2JA8sToh8+4pGhdkDSIiIiIiIiLyPjYBI+fY0dxKpUzWzyEiIiIiIiJqxQQQaWNlDRs7mk+xLx8iIiIiIiIiVUwAkTopgRW/W5iw8V6SJmrkvUkJrPzd+mCIiIiIiIiIbMIEEKmb9y3w6SXAjE8sLtj+BlpaU01bapv0Fz7uFWDIffpfR0REREREROQSdgJN6ipXKX8rSqwpL95My0PNyZojBl6/YY6pdRIRERERERE5jTWAKDsPNwGra4oAACJRy4tWxyHgiYiIiIiIyGeYAKIMhMpjszIkUCrXAPUVscWyJ1oWbqgGAGysbrAiMG02znNuXUREREREREQWYAKINHCwxstrfwLe6KE8nvuNhheYTUwZeG9bViSs3nsdWxMRERERERGlYgKI1CX12eNgEqhus/K3bL6OF7FZFhEREREREZEaJoAoA4trtzhYW8axdBD7AyIiIiIiIiIfYAKINLA4yWFp0sSCsrZuAsKN5sshIiIiIiIi8igOA0/qEmvsWJK0iZdnR60ZY7WLBAC8vC+w/3nGVhvvsJqIiIiIiIjIw1gDyGUj5m/Aob1GoKE54nYo6qyqsePBDpNlPHG0ZLixAhqqrAuGiIiIiIiIyCZMALns+aELUdMQxvoqB4cx18ymhI3mhJLRWj3sl4eIiIiIiIgoERNAbpMS7eDF5I8XaEnkZEgSRaOWRUJERERERETkZ0wAuezG5i+xsPhmBBoq3Q6lLduabNlfQ0cAwK9P2L4eIiIiIiIiIj9gAshlZ4fHAgACDVtcjiQDT/cBlCG2WQNtWF/q2tncjIiIiIiIiLyPCSBynqXDwMeKtKu/omzrteG9EBEREREREVmNCSDSyMph4O1Y3qUEkEvrJSIiIiIiItIj5HYApPBmTZJYcmPSm+6GkU5zA/DsLjhaZbbWT5MJHCIiIiIiIsoHrAFELrAg2dW0NempEO4k0DjkPBEREREREfkBE0AeNnj2OizZWONeAFZ32mzbqGKwpV8hIiIiIiIiolzBJmAeka4myT+/mAkAKHnhQqfDyUxKc8kcp5I1DqyHTciIiIiIiIjID1gDyGXeTiBYHZt97/XomlGGXme2CVcQUeDLa02VQURERERERGQ3JoBInW1NtnKsudain92OgIiIiIiIiCgjJoBIP6NNq+zsA4iIiIiIiIiIVDEBRBnYlLCxpG8ea2KTTEoRERERERFRHmACyGX5NYx4mmTLt/8Avr8j/eLj+7Q+nvGZvlVJCdRv0fcaIiIiIiIiohzFBJBHeLIzaNXaMRYmreYOAmYPzL7cT3drLtKDnyQRERERERGRq5gA8oj8qglERERERERERE5iAshF9w+ajaYIEz9EREREREREZC8mgFz07YzSjPPfLHgNlwfGZi9oynvAD3daFJVLVk8C3juz9fnUD9Iv11QHvHsasG5mxuL2nfOyptV2kWVaIyQiIiIiIiLyLSaAPOzC4BS8UvhO9gWH/geY9bkNEaj0pmPHMPA/3wusnd76fMh96WNZP0v5N+LhjKvqvvg9IxESERERERER5SQmgDyCDcGIiIiIiIiIyC5MAJG6TDV2zDBag4iIiIiIiIiIDGECiAzQkcDZMBf44S4gGoVTA7SfE5yefSGrVWXuz4mIiIiIiIjITUwAeUWu1or5sicwawBQuSrLglmSQ3bVRrLKyCfcjoCIiIiIiIhIFRNALpMO1YoxxJKkS7yMxARXDia7cjWBR0RERERERDmBCSCyVzyJJKW5hJLnEyxej4+IiIiIiIjyGRNALro1OBj7BNa3nTFrILB0ZPoXNdUBQ/8LNNYoz1eOtS9AtdpJCwcDc7/J/NLazcCwh2J9/8SkJnHqK1ofR5utic0t8793OwIiIiIiIiIiVSG3A8hnjxR80foksXbMD3eov2hKf+Vf0XbAWY8Dn1xsX4BqvrlJ+XvoX9WXGfYgMC8hSZSuBs9vT7U+3rzEmtiIiIiIiIiIqA3WAPIbGUn+ayczTbba1OhJ0wQsGnYmFiIiIiIiIqI8xwSQVxjo46asusGGQKySkrDxfB8+RERERERERLmLCSC/khKX9JtgTVmLhgDvnQVEUmvtmKh106bGTkICKFeTQQ3VbkcArJsFzP7K7SiIiIiIiIjIY5gA8rENVtUA+rInsHYaMHOANeUBSFcDyNND3lth5BNuRwD0Pw34/la3oyAiIiIiIiKPYQLIr+zoEyfSZH2ZLSSWlSkjl5XV6E9c+SJ51FTrdgREREREREREaTEB5AODpq1pO9HrzahSE1RSoqymEQDw85x1aGjW14l11Ovvl4iIiIiIiMjDmADyiEz5jQe+mZPwzMGaMNlqGWXsa6ZtH0AiVt7c0iq8+qvOYd/9kADaugGYM8jtKIiIiIiIiIjaYALIdzyUCPn+VqC+Mv28NDWAEpNCFbX6mpsFhYfet5qVY4Hv/qH+mRARERERERG5hAkgykBDbSMZ1fhaiYCXkld2Uv1MiIiIiIiIiNzBBJDv2NgEzMpmVmlqACVOktLY+uatrTIXlxMEf1ZERERERETkLbxS9Yhtlw8Gwo1uh2GNJSPSNIOSloxc9r/BC5TS7BgFzSpejo2IiIiIiIjyUsjtAEix45SXgUA9cN5zbodiTt0WYOCVbafLKISFtZciUendjZc1gIiIiIiIiMhjeKXqJdWlbkdgXkS9c+d4xRgR7wsoZ2vK5Or7IiIiIiIiIr9iAogsppL8kBIyYV5Odweds4ktIiIiIiIi8ivPtqIhFSXjYg/8lkJJjnfbcAWwZY5LsdiNCSAiIiIiIiLyFtYAckkkmi6BkyVxsHYGsHyULfFYRq32S8LbFQDuXX4zsH6WExF5mpQSL49YjHWV9W6HQkRERERERDmMCSCXHPLkcP0vqiu3PhDLZUpitc7rGPbDezFKvXaWlBLlW1tHe5u/rhr9Ri/D3QNnOBEYERERERER5SkmgFzS0Bw1WYJHmxmp9n/jtyZr9hgweTWOfuZXLNlYAwCQsY+lKWJ2eyAiIiIiIiJSxwSQT/26cKO9K6jdDCwZYV15UqJr41IAgBC5nQyqqmtWnTduySYAwIpNtU6FQ0RERERERMROoM2IRiXKa5uwc4cia8qD0JyRW1a21ZJ1quq9j8EXqtQAmvU5ujSuMByOn0Sl/gSXgZcQERERERERacYaQCb0GbkExzz7K8qqGywpz/akjhPUmoCVLWx5KKVHm69ZRM8o8BwxnoiIiIiIiJzABJAJ8WZYm7c2WVJeTYN60yGF3dkCZ6qh5HoTMJHhe0p956z5Q0RERERERE5gAsgH2sOaGka2iDQB1et1vWR3bDa2rqa61sderjqjIbTU8L38doiIiIiIiMj/mADygbFF9+CBb2bjho+muB1KWz/eDfQ5EAg3Zl825t6Cbw2tquqtswy9zmlakjmpNX9YE4iIiIiI/GDQ1DV4cfgit8MgIgOYAPKBnUQ1Bk0rdTuM9JaNVP5GsjWDM5/h6Fi5wHQZXsOaP0RERETkJw98Owdvj1nudhhEZIDuBJAQYnshxFAhxDghxDuxaR8IISYKIR6zPsT8IW3v48cBahmNvKrikv29MvFDRERERERETjJSA+h6AAOklKcA6CCEeABAUEp5IoAuQoj9LI2Q/KElwcPMhpFPIK/yY0REREREROQ4IwmgcgAHCCE6AdgDQDcAg2LzRgE42ZLIKAuPZgxUq7Z4NF4bCFbvISIiIiIiIo8xkgAaD2A/AP8CsAhAEYC1sXnVAHZJ9yIhxK1CiGlCiGmbNm0yEit53MTlm9F/7Ir0M/Ooikum9I/ax8CcEREREREREdnJSALoOQC3SymfgpIA6gmgXWzetmplSin7Syl7SCl77LzzzoaCzX16sgDeyxj0fG8y+o5apjLXmgRQrjQ083v8RERERERE5C9GEkDtARwqhAgCOA7AC2ht9nU4gBJrQss/UleSxPoaNfXNEcvLbGVNyiNXEiep314eVZAiIiIiIiIiFxhJAD0PoD+AKgA7AHgVwPVCiD4ArgQwxLrwSM3toZ+xl9hgbaE+SEJ8XfQUACC4eZHLkWjUqyPw8UVuR0FERERERER5TncCSEo5RUp5iJRyWynlOVLKagCnA5gE4AwpZZXVQeaL9VUNGLO4THV+an7mEFFiazxG5EoNHSu8PGKx8qBkXJt5/JyIiIiIiIjISUZqALUhpayQUg6SUlpcJSX/3PjRVBfXbmcVIB9UL7JYv9Fq/SEREREREREROcuSBBC5w1u1SLIkePKok5v8eadERERERETkF0wAeYjUmdJ5s7CvTZHYYN0MtyNwToZk15/qJqOkuCeK6lhZjoiIiIiIiJzDBBCRxcIRifKtjWnnnVqj9JHesWJu0nTWGiIiIiIiIiI7hdwOIB9UNzRju+ICt8Mgh/zry5kYu6pB07LCW+34iIiIiIiIKEexBpDNhs/bgMN6/YLpqyrcDoUckum7FqzrQ0RERERERC5gAsgCmWpx/LF8MwBgbmll1nL+HJyIo8QSi6IywEx1lDzq5DmbLqIcJcU9cYgoUV9ICAyZsx6Dpy7F4qIbcGzTFMfiIyIiIiIiovzDBJAFrMx93Bwabl1hejGJY4kzAzMBANcEf8u43F0DZ2D8pD9QJJpxXcPnToRGREREREREeYoJILIGO7NpkbGZF5NsRERERERE5AImgDzHpwmCWGKDfdwA8VSYhHpSLHUO02dERERERERkJyaAfOLq4Ci8W/Bq5oX6HgWULXImIMoqfQJIxOalLsPEGREREREREdmHCSALONH66YWC99FONGVeaMtyYMJr9gdDGWWsBSWS57HGFBERERERETmBCSALsFsX0qxlW2GjLyIiIiIiInIOE0Ae426NEGayrJH9c2zbTxATQkRERERERGQfJoCcVlUKDLwK7dHgdiRtmEpBTP8YANBFlFsRiq9l6tXnyPo/VF7F5BsRERER+cfeDw/B2CWb3A6DiHRgAshpo54BlgzH+YEpbkdirV+fBAA8EPrS5UC8I9MoYJnmERERERF5XVQC/UYvczsMItKBCSALONEJNOWW1qZ+3HiIiIiIyHlTVm7BpBWsvU+UT0JuB5ALrOwE2nw6gAkFt3FkLyIiIiLyuivfVbomKHnhQpcjISKnsAaQzYrDNXg69CGCEW19/hwfWGBzRBnEqzJxWDNLZGrmdcCMXmjnwX6giIiIiIiIKDcxAWSz0zd8gOtDv2K/tT9oWn4HsdXegDKJJ37qWBXUDC01gIrry3BTcLgD0RARERERERExAWSJTH0ABWQ09iiWFLC9do3x8iOs+GMJrY3wEpcTrHVFRERERERENmICyCVevNyfs6bC7RDyjhe3AyIiIiIiIso9TABZYG1Fve7XHB1YakMkAOZ9Z/il4ahTtZRyW7wJ2FXBMa0TJ74BVKxKsywRERERERGR/ZgAssAtn07D19PW6HrNtaHf7Akm0mhPuaSZEEoCqL1I+C5+eQwYcLlLEREREREREVG+YwLIIi//stjtEKyTqVOjLDKNfJX3mpI7+JZgEzAiIiIiIiJyBhNA1EqabwKmZQSsXKeeAmNyjIiIiIiIiNzBBJAdFg0ByhamnSVzOEFyU3AYAjn8/rQ6VizS/RpXE2dSAlPeAxqq3IuBiIiIiIiIbBVyO4Cc9GVP5W+vthfUy8q2Yj+Hw3HKkwWfuR2CJ5wQXJB+hommdbZaPQkY+h9g1UTgio/cjoaIiIiIiIhswBpADqusb3Y7BHJNagLIIwmhcGwUu7pyd+MgIiIiIiIi2zABROQib3Sa7YUYiIiIiMgpE5dvdjuEnLC1MYznhi5EYzjidihEmjABZJGN1Tkw/LpXmyjlCumhA8P6OcD62SkTLeiHaO10YMSj5sshIiIiItu8/P5n2EesTTuvKRxFQ7OHzls97LWRS9B/7AoMmlbqdihEmrAPIIcJEyNs2c7LseWCmvVuR9Dq3VOUv72qWhN/Vnz/752p/D3xn0CHXc2XR0RERESW+66oFwCgW8PANvNO6z0a66saUPLChQ5H5T/NkSgAIBL7S+R1rAFElPdsqPkVabK+TCIiIiKy3fqqBrdDICKbMAFElO/Y9I+IiIgob0kp8dkfJajiYDVEOY8JIIdJP1xsR8NuR5AX9hIbcXNwmNthtGITQCIiIqK8M3NNJR7/cT4e+naO26EQkc3YBxC10fz7yyhwO4g8cFVoTMIzN5Mv8aQkE0BERERE+Sbe4XNFHZvwE+U61gBymKc7gY4ZN2Wa2yGQk/xQK42IiIiIbOWDyxQiMokJINv5Z0/aWg+ECQHn8TMnIiIiIucJnoca5p8rPSIFE0Am7YZydEZF+plrZ7izO926yY21kikmDx8bFwBNdQnFGSiPt32IiIiIFFICpdPdjsIRMnYeult4DdBQpeu1TB0R+QsTQCb9UfxPTCm+K/3M987AsZu/czYgAHh5X0Mv4+W/e0wdPJvrgbdPAL65yeTauQUQERERAQBmfga8fyawaIjbkTjmtU3/AD48T9dr8v3skQkw8hsmgKiNfN+R+05E6bCvcfk4Qy+vblRGfaus49CfRERERACAzUtjf5e4G4cDkpqAlS1wLxAish0TQNSCfQD5W2M42vpER3OulZtrAQAbq+utDomIiIjIn4KFyt9IbtwgGzx7HW74cIrbYRCRyzgMPLVgzZ8cU7cFEAGgXafk6RWrUhYUsf9NbgG15eZeT0REROQVwQLlbzwBtGUFsH13/4yeunUTUFAMFHUAAPzzi5mqi/rlLRGReawB5DAmWchyaWv7SOCl7sCLeyVPrlwDvH5YyrIi/gpzeu9ttgQiIiIibwjE7pNHm4GVY4G+RwKzBrobkx4v7wv0O0bTombGAWHuiMhfmACiNLgrd0NjOGKyBA3fW21Z21eJ+KuZniQiIiICkFwtZtNi5e+6Ge7EYlTNercjICKPYQKIyAOawhEc8NhwNCX24+OU+AmOpfkfJhGJiIiI/MBME7B8v32Y7++f/IcJoFwVbnQ7AjKgKWJRAihdXd66LSoL2zEMPA+H5ALVbZyIiEgnM+2ivKSxJvl5fQUQdeGGIxF5AhNADnOsmc2bxzmzHvKHxcOUPoFKJrSdx8o6lAtmf6Vs4+tmuR0JERHlFJ+fKD3fteXhjqgCXuyG6OjnLSve55+Oafn+/sl/mADKVRUrDb80R+535Lwhc9bjx1lrtS28Kpb4ydB2nQcw8rUVo5W/ZQvcjYOIiHJM7pwZ7ySqAACbp33jciRE5BYmgKgNyVSAa/R88ncNnIF/fzlLZa72kxXRshvInRMcIiIiIkqvttHswCNE5FdMAFGrXGnr7EPxpoFtvgEpNbTT1vG9pf2OmfAjIiIiSi9XzpMkAirnjGbeIa8eiPyFCSAiLxv6H+Cp7TUtmngAbly/MP1CC35QfT2HgSciIiLKAZVr2kx6PvQ+hhU97EIwROQlTAA5Rsmt+6F5lR9izFVtPvmp7xsq57G3P0t6Hs2U2wnEh4G3MgHEbYiIiIhyjF9qy29a3GbSNaHRLY+1nus3hbOPFpbvZ3w+2SKIWjAB5Bhl98BaFuSGuWurVefZc+Dmdk5ERETkjsznYVqvR/76zkQrgskLQuR7Koz8ggkgaiFT/pK3jF+6GX/uNx7Nkex3Y1LVNYVV59U0KvO8fthqDEdQ38ROC4mIiMglfrnIt6im0pzSKkvKyQfSL7XDKO8xAeSkL65Bj+pf3Y5C1aklrwO993M7jLymel7xRg8UD7wUs0ursKmmMe0iHUWdoXU+NzReTdjiA9cfbwG9OgLh9PHqdXrvMTjoieGWlEVERESUmZ8v6DPHntgEbHDhI7iq/yRcHhhrd1A5JxyJ4rsZa90Og0gXJoBM0J3oXTzUljgsVVvmdgR5KX4YVt2mypeih5yrLGPxuuPlmWmemLaN+LiXlb+NNYbLTbS+qsGScoiIiIg080utn0Q6LlIODZQAAG4ODbMpmNzVf9wKbG1Ur2VP5EVMADnGPwcPdgLtbUaqmNr9jfYescjmNRARERG5IAeb9vBM37xfF2zE8Hkb3A6DSDcmgEzQd0PAPwcP/0SaewzdZLLoxMRMKWu21Cc9/2VB2wNiVX0znh2yQNOIEkRERETu8n6apKy6QeXGoPduFuaaWz6dxj6SyJeYALLIo6EBbodAPrZfQGk/vHpL5n58OqMCXV/fDZFVk/BmwWt4r+CVtMtpbc41enFZS40vw03AfnsKT66+MWlSr58WtlnspeGL8N64lfhxFttKk0Wmf6z0MzXtI2fW9/7ZwJD7nVkXERG5zNu3ROeWVuHY537DV1PXtJ35xdXJz3t1zFoeRyomyg9MAFnkHyEf9O+jEZuAuee818ZlnH9CYD4AQEx9DxcGp+Cc4HRN5UqVqkXLy7bC9D2fca9gt+bVWReLj14WzcGq1OSSwf9W/v58jzPrK50KTH3fmXUREZE3eLQPoKVlSh+Lk1ducTkSIvITJoBMSL2O7fbQEHcCIbKChXkZ3kUiIiKinJB4wu/Bm1h2Dz9+8Rvj2dGxBiJDovDOz6fj8R/mORgNkTomgCxm906YCAC21Da7HQIRERERucSpiklz11Zh4rLNzqzMxzJdAw6duwGfTVrlYDRE6pgAMuHw8Jw20x7/Nn2TnL3KRtkdTnpjXgC+u82ddZPl4sf6FZu3ZlzuiuDvLY+XldVArZlXt40jMbjw0eSJ62cDrx4K1FcYjvO+gq/bTGNulHLGgh+Bd0/jRk1ElGtmfwl88H/J0xIzLU43B6teB/Q5GChfrrqIkSNR92hJ0vPRhffioED25vz54vjnfsNdn89wOwwiWzABZMLt9e+1mfbH9PQ7i90qptodTnpjngfmfOnOuslGmU9AjgksaXn885z1qsudOf8RBIRy6tByAvH7S0DVaqBkvOHoLg+O58Ux5a5vbwHWzwIirIlHRJRTvr8NWDPZ7ShazfsWqF4LTPvQ1tV0D2zMOD/fzug2VDdgyFz182ciP2MCKM81NEfSTPVmZ3fUSn9uJf0LpM5D+ozVFej20BCsLs88WhmR45xMOAYKlL+RJufWSUREzsq3rAcR5QUmgCzmp85vF22oxoGPD3c7DDLAsu0soZjmSBSv/bokY1Lo62mlAIBxyzZlL9ujo2YQmRZkAoiIiNwlYjdsWeGaiPRgAiiPzV2xFp8WPO92GGREQm7lvkEzsywqoKVWVyQq8dqvS1HbmK5WGICGKvx9xb+xG8p1BErkELsTjmULWx8HC5W/TAAREeWu+GFl0VBg6H9cDSWdtIe9cCPw+RWmy+5T8FbScyaZiHIHE0B5bNe1I3FqcG6b6dzH+0HrUX/Uosy1cSQkFqyr1lG2yhYw71vsu3U6/hn6XmMx3JIoh/x8b+vjQFD5G1VJlhIRUe7YtDD7Mi5KOtsqnQos/cV0mX8JGu8Hkoi8jQmgPBaJRtNOl+wDyPP05laaIum/a2co21NjWImh94jFLsZCZIX4PpJJTiKinJX3u/i8/wB0ETprIg+bux6n9x6NSJSfMzmLCaA8JlSyCH7qxyjfWP3d6Er2mazRU9ek1JbYvJXNZsjnROzQyVpuRET5JY/2+7l4PdAYjmDhej214rWTOreNB7+dg5LyOmxtCNsSD5EaJoAsdmRgmdshtJr7TcbZQqSvFXJxcJId0ZBev/duM+mRgs8B6LsnIyAyJHo0lhSNAsMfir0iVtbKccCE1zW8WFkH+4Qmy4x6Blg/2731tySA3KxZRwTlYvTXXsDG+W5HQkR2ciHxlIunbY//MA/nvz4OG6sbXFm/3iQRkR2YALJY74L+bofQ6tu/Z5ytVgOIPGL0M20m7SzsuWsBAIFYoiYcUf4mHaTWz2rb4e0nFwEjn1AvMCXjk4snEuSCaAQY2xt491Rn15v4e2hpAcYEELmssRoY/yrw4fluR0JEtsh+9pScVLDubCsXawBNW1UBAKhpaHZl/WOXbnZlvUSJmADKY4IXL74lkh5bc4CO1+xZtKEGADAvqeNoA+tISTCmqwEUjkTx+eRVCLvaRxGRTqwBRF7DbZHIUvPXVaWf4Xh1ZvXzr/R9zliXtEk+v2x9XNeUC02W3Lkt2djMwSPIfYYTQEKIt4QQF8cefyCEmCiEeMy60MhuAjxhpFbxA3041jl4c8SqkwgR+7/twXbApFV49Pt5+OSPVRlLYJVZysrJbYR9AJFnsG4lkR0u7OuxUbBcaEevtsZr+rOriHRqmyJoYIKHfMBQAkgIcQqAXaWUg4UQfwEQlFKeCKCLEGI/SyMkojZ2bcqcMEm07+ZfcWfoJ5W5+k8ojF7ypjt3qaxXquBW1Weuijtg8mqDa6Wcs2GuO+uNJmyjrAFERJTTTg6oHGvKlzsbiIvUapjPLlWpHeUHWU5iPxy/Eis2bTVUdO8Ri3HOq7+bWT2RI3QngIQQBQDeA1AihPgzgNMBDIrNHgXgZJXX3SqEmCaEmLZp0yaD4RIRAOzVtFTzshcuekjjknYdltTL/Wn2Ok0lzFxdYVUw5Hf9T0s/3e67o2unJ65M+cMEEBFRThpQ+Hz6GStGOxuIBikN7i0rNzEBlGsVXtOdMjSFo3jq5wW4/O2Jhstds6XeRFREzjBSA+hvABYAeAnAsQDuArA2Nq8awC7pXiSl7C+l7CGl7LHzzjsbiZWIHFDbaE/11XQH2xWbanWXs3Kz/tcQWUowAURek2NXZ0SUld2NwnKxE+gVGc4hZez92nUeTOQVRhJARwLoL6XcAGAAgLEA2sXmbWuwTHIDx+X2pN4jFuVYG2Jrt7PGcC59NuRL8SZgOXhyTD7D4zgR2XQoSkwA5cKuxgt9F+VaTSryJyPJmmUA9o497gGgG1qbfR0OoMR0VOSQHNib56A3Ry/H/7061qG1tT0SqbZ7N2nP+kV4u+BV7IbyNvOybok8YJKXVK9X/rIGEBFRDvPQyUeazIHdSZnE4jMlLvySHCpfOQu3BgfjssC4jOed0kvfO5ENQgZe8wGAD4UQVwMogNIH0E9CiC4AzgdwvHXhEeWn1VvqgGJn1xk/GG4jGjMud3hgOeYYKP+h0juBILC/KIXSkpRIp83a+76yVWOsA0wmgIiIyFbuZVe0NgHzS62WX4oebHm8Au4MXO2XZBnlNt0JICllDYArEqcJIU4HcA6Al6SUPu4aPj9c+uYEbKxuQO/u3AvlAnPfov5XF0BvE6zkM4MdRbXudRIBAMKZk5NEecsvV2BEHnT52xOxffsCvH/DMSlz/HGebFeNlVzsAyhOZMjECAh4qvYXkcWM1ABqQ0pZgdaRwMjjZq2pBOCXwxo5RfOdHgCz11TiWpvXQ9SW/dtOdUMzahvD2K1ju+wLE7mOR3Iis6avUhtp1AvnK+oxCJt//0lNwGxdk7fY2QSMuXryAnbYnIdOCMxHN7EekvUQc0IBwpaVdaBYrWm5QdNKtRc65ytg3CsGIyJKkOnMyaKzqv/rMxYnPD8K5Vs11DbimRy5REqJmavVLlqJyHWT3wVmDbSuvAzn7HYdijLdsNtXlOIYscieFbvE7oQakVcwAWShrqLM7RA0+aLwWYwpuh+8c5gb/hX63rKyhhc9pGEpndvNiEeA354yFA9RMi1nueb2axuqGwAARz/zq6lyiOw0YPJqXPbWRIxZ7I/zDqK8EgkDwx4AfrjD7UhMyZQA+rXoAXxdpJzb+fF+sg9DJrIME0AWKkKz2yHo48c9tkd0a/jc7RBa7CwqLSlHexMwZ3sdqmsKo66JQ78TNN7mZK0cyn3LNtYAAEor6mNTuN0TeYd7v8dw1LrBCXKtE+gkLgX94vBFqKhtcmXdRHFMAFnIf32bMAFkXG58donJHK3vyOmt/OAnRmD4/A0Or5W8KQfGoSWyErd7Ig9y5neZ7ue/eONW68r33XWNHu68t5Wba/HUzwtcWTdRHBNARB7x1+Dv2BkVOFws0/W6fcQ6w+ssSKi1tl9grabXaK8BlOXgumUFDoj1OcRrGPKnXD45Ji8TMoKrg6Owc+Uct0MhIidkqLFiXx9AaZROR2f4v/+xTOeddlcOaopYV0uLyAhLRgEjIvNeLngXjaEQikQY3Rq0dxy4T2C9jVG1pfm4WJ9lVI2+R2JEEXS9V8pzvqxnTmS9E8q+wrkF7wMz3nc7FKKctXpLHfZ0O4gMN93svneWWAOo5fD7/pkYXVSUvJwfb+KlOZ+wc/SvRH78uCi3sAZQnrnz8+mtT3y5x85tRcK6Eb385LVfl7odAvkCE0BEANCpKaVZLJOjRJarrjfat6d7v0cnzuy3ERpGyfQ89e+Il0eU65gAyjND57IvFSLyKV7jEhERqbLyMKm5wb8Pj82Zhnz34/sh0oMJIAsdLla4HYIuTHCTEVaMArZoQ7WJ16esf9mvwEZ2qJcfPHZWxrNEIiLf+7/AVHQTzjan1y77caal6dLaGRBRe0Ykdqp5lGNUjt8HitVojwb7179xPtqjHu3QgEDZPPvXR5SAfQBZ6JXCd9wOQZfFG2pwkttBkO9ICGyD+uwLZnDea+NQUmx0/QkH7aq1wIDLlce9qkzFRD6QKeHCZAzlEck2CkTWqK9E/8JXY09uSZlp8LiSeDwqWwR0PtBYOYnS/Objk6QEUL4ceO8M7LW9BevKV9Ewhhc9hInRQ9Cz6VHbViMA4O0T0Q8HYWtBITp8PBt4dANQ0M62dRIlYg2gPLZgQ43bIfjOtOj+OKDhY7fDcJUEUAR77jDp1mi8JhH5kZaTcV4YUz5iApTIkIjN5zO1m+wtP66uHACwTcUiy4rUOgy8H/PRQqTpBDoSAQD0EItNl79ycy3GLC7LuEwPLESPQGxd0fzsA5TcwRpARDpEEEAjCt0Ow9e0nlB8MrEEh3XtaHM0lHt4IUxERBoF1S+FrGn2xGOSJ2WsNWz+Ozvj5TEAgJIXLjRdFpHVWAMoXzTVAgA6Q21obvKS7VDrdggAACklNlY3tDlOmjk0ak0APfnTfFz21kTtBVeVGoyIcoIrtyB5Yk/OCkei+H5mafprl5oNwNoZjsdE5GdRI5dCm5dqTyBY1Tw5bTkiy3xz9tbYL1LOtMBOOY8IIgJs8Vf/rkRaMAGULz69FAAwpfgud+PwOa3JC7PmFP/DkfVk0/3hoTjuud8wftnmhKnmLrRtGz701UPsKZe8I9NZZuVq5+Igcsn741fi3q9mY9WmNH2evXIA8N4ZwJqpzgdG5FObtzapzlMdKapfD2D2lxrXYPa8Mfs5l11npl8VPY0LApNsKt1taT61lHOMB0NfAn2PBCrX6Cr5wr7jWh6/OXoZotHkcgfPWdfy2KnrCqJETADli9IpbkdAPra2IrnTZ7MjgREZk+FEaWvmtvZEuWBzjZJAl5GU/iISL1wqVjoYEZG/BTKczmRsArZhjvXB6ORExdeDAsrNlZyp5aPDCYH5yoO6zZkXTDF/XWv/lL1HLMYvCzZoeBXPq8k5TAAR6ZCviY9IwpHf7c9A9Y4c5b58PAMlSiBT/hKROcFMGSCjpA1NwFyipYaKLzuBTve+bHojtw9g01zyFiaATHD7QpjIKYnnLwUIY0dhbvQtM30ctdyRizQD9ZWm4iCfCddnXyauoRpobrAvFoBX4eQinn8QWSFgRwIoaUQnfx8okhIljbkzerCbTa/Y7IvcxgSQCfwBU76IJmSA/hQowW9F/zVVniV9HH19I/DReebLIf/47LIMM1P2xy/sAbx/tq3hEBGRv2VM/xg9zf/w3IQylEKawlGDhWUPws5KRvHPRwLA810dX78bmF6nXMcEkAmNhnfm7hg0VV8nZkRxUS8e3Rf97HYE5CXpttGNc52Pg8gBbWsge3AfTeQLNvx2Ns5LKn/4vA3Y/7FhWLDORO3pNM2TnEhU5NPN7tTTiHSfbzQqEY746/qPKBUTQCb4rQnYA9+632Ed+dPKzXVuh0Ckkb/2y0RE5J5M97cy1w7SnhgZvUgZpGBOaaXm1+gjYXcSONNn4c8+gLQrr20dKe76Dydj30eHWR8QkYOYADIhn7LilN9mrq5wOwTKd5FmjQs6uV/mMYCIKFdZsocPNyKIMIrRCBlpBiJhIBqrQRKNKP8SqR3rpGydF2kGpMSsNZVWRJhRAcIIIgIpc6vWi9SQwIsvsSUhATRhWbmlcQSRW58r+QMTQHnkpACbQxCRD21eBjy9U+Zl/HgLkoiI/EnrMefLnnhu3hlYVHwTrhlxFPD0jsDHFyrznt4Z6NejddkN85Rj3cLBiStS/lSUKPMmvaP8HfcK3hqzPHkZG9wSGoblxdfj+Im32bYOd3jjBk6x0Hpzi8g6TACZ4LcmYKcE5mVfiMjjOAx8HmJfPkQAWludtLl08WI/bUSU3uqJyl8ZAbasaJ2+LjZc+JLhbV+zaaHyd+r7yt9Zn9sXXxqdy8arzsuV3U9qLSdHzzZ5E4scxASQCWwCRpS7GsMR1DdFsi9I+StXznqJiPKVX/bjGeL8deFGG/sXylE6vvdIFHhq8AKUVTfYGBCRc0JuB0BEpId0KPF6Ru8xWFfVgJIXLnRkfWSSX07iiUyI3yT2Ww1kItIg43EsNk+lpsj/Bi/At0XWh6SFHyuvaOkDKG52aSU+nFiNkvJaS9btw4+LcgxrAJngtxOw1F3dywXvuhIH+cNRf9ztyHpKinvicLEM+ONNoFdH5V/NBmOF9eoIbJxvSVzrqninh7L44GzgvTPdjoLyiJTAxYGJuD70q9uhEJFt0lxfVJRkXIatEoyTUmJ9VX3L89TPUkaV55EoP2PKDUwAmcCdLZE1zgzOAia83jrBTBJn5VjT8RBptna62xFQnukZHJVmKs9HiPwv3e+Yv217tH6u745dgROeH4UVm2pVliDKLUwAEZEH8bBLCTRV1eY2Q6TwV+1kInd58NiRsU1VfJ4H4/apCcs2AwDWVtQlTc/0LURZG4h8jH0AmeC3JmBEXhaOJuyQeFwlw7hfpvwjkbjlcwdKpJnH+49rjkRR4HYQuUhKTFm5BbtuV9w6SWVREUvIJc5/7dcl9sVGZDPWADKBTcAo140r/DceCn3hyLoq6xoTnqn/trIOAz/8IWsCSjFzdQUWbai2pWzKwo89TBLZQK0T/Gg0mna6JywaovTPVl/pdiREutiaG3qjh6bFZq6pSp6webHyd+smiwPKLwISV777B07tPRqHNUxDSXFPFDZuaZn/YcFL+FOgRPX1P81eZ3lERE5hAoiIVO0R2ITbQ4MdWZfXa9Ne9tZEnPfaOLfDoKw8viER2cDTlRjGvaL8LV/mbhxEabj22ylfqmkx1aZGTTUWBpN/Er/382q+BQBsV7EAgJIcOjM4q3XZ2F+maChXMAFkApuA5R9+5/aQSL5sl9LDd7OJiEg/T2epiDyAvxHnpP2sM3/+Vn07bEFCbmMCyAS//YCZvCCvSt0yl5VtVV1WrQkEERF5ETutJX/KeJ5va7JG//k6z/CNa7k+Urn5mO6zLSmvSzOVyB+YADLhoMBqt0Mgh9XK4uwL5aCTA3MdXV9jc6TNtP+GvsQbBX0djYMcUjIBeOUgoFEl8WfmRPvbfwC/PG789VqUL7e3fKIsEi9Uw9M+di+QdOJ9eG2cB/Tel32XkLOkBN46EZjztdoC1q3r21uAkU+YKKBtLMcv62OiPPvtJ0rdDsGQi/uNwycFL+C24GDf3dAnMosJoDzCHZxxi6J7AADeCl/iciTueKBgkKPrS9cE7K7QT7g4OAlz1lShorbJ0XjIZr/9D6hZp1wgWm3uIGCizYnDmZ/ZWz6RDqHVE9wOIb2J/YDaTcCykW5HQvmmbD7w3S1pZxk+M043OMHcr4EJrxstMXPZHnVDcITbIRgiAJwWnIOHCzQMdOKfr4NIEw4DT6RBGEEAQCMH47SNTBrEWP2U7IFv56D779tgtBNBkTf46GSYyA3K/tPrN3m8Hh/lJBM1SB1vcs4+gFwRP/+Uap8/vxbKMawBlEfYB5Bx3Pfbq83nm+UDX7m51q5QyE1mTn5NnjhPX7UFtY1hV9ZNpJU/NzWee5CbfPmjIZsltorgHoryDRNAeeScwHS3QyDSRCRc5dwV/AF3BH9Kmt8eDU6HRE4Yb6Kvg4qVsQc6TuWGPwJM/xiVdU24/O0/8M8vZhpfP5GXLBrqdgRt+TN7RX6XZbtTrfXhhiH3tT6ORoEvrsm4+Laow1eFT2FPsRF3hH7KuCwlSzxT2OJAtwLboB5fFT6F7mK97esiyoYJoDyyX2Ct2yH4Fu8OOCux2vV/CwbhwYIvk+afGpjjdEjkhKW/OLu+SW8Cg/+Nhmalz6n566qcXT+RXb7MfOHoKMFRwMhNWbY7owkguxNHjVXA4syJ3LMDM3BcYBHuDX2DM4Oz7I1HRS62Lkh9R9/MMN/R9WmB2TgusAj/CX1luiwis5gAItIhFw90XpD6qXrqjhw5IMvvStf2wG2H8g+PTUS5RNvvOX60C7h43PPrADOJcWfrA6iuKZJxvpl1t/Ln50j+xAQQEXlPloOsX084yNuYdyS/4j6RSIVdO3bbByfIXn48ccHfv1X4OVJ+YAKIiFzXAXXYVVQkTMl8EL46yDHA8gpHASMCABSHq3FCcIG2had/bGss2sV+vzKa/JxIqwmvA8tHGXxxlj6AjL/UPtM/Al7cK+tiXkgAXRf6DdtGq11bvyazBgKzv0yZ6OxnlrjXO0CYb1JGZAYTQETkuptDw5OeZ6tme1owex9A89ZW4flhC9mcjDQznmfiNkbOOHXDx9oXHvxv2+LQhQlcMmvkE8Bnlxl7bdZzgEzzvb1vj8Yu49yuAXRF9aeurj+rH+4Avr8taVK6vdLSjTUZixEW7MskBD4vfNZ0OURmMAFEpIPbB9n8Yf5zvvTNCXj39xVojvA7I21SrxMqHBgZhEgPtWOQL/oA4q6YXJG7G54X+gDywvqtsqmmEQAQECr7WQtuKPI6gryACSAi8hwra+3w5jNlo7aNTF9VkX4GkUuEL2s0cidM3pXpJ+X1xKpXagAJRLMv5DHpPjPp0Ofo9e2Kch8TQEQ6cKftvgdCqe24zRm7ZBO6PTQEVXXNlpZLOmTL0ll40RttbsQnva7D9xMT+lGREncFf8DucoNl6yGyQl1TGKvL6xKmpP8tFIiIMwHpsXIsMOsLt6OgfPXHm8CGeaaOH2MWl6nP9EAy9r+xIcX3FutdjSPgwwRQItnmgX0uDE7B9mKr/SsiyoAJICLyngwnVneGfrKqKABAv9HLAAALN3i8E0PSKHMyKTLrC9yAwagd/mTLtEBtGf5bMAh9w08bWuMH41fi7D6/G3otUSY3fzwVp/Zu7fTe7Tv9unxyMfDD7QkTfBQ7+d+IR4B3TkIub3f7BJTEzwEBdzsVDkj/JYDS7UvV96+8+Uu5hQkgIvIcK07X2PTLPxztqDuq1JQIIaHGROzktQjG+vxpjkgsK+MdPbLepBVb3A7BvPjO2AM1JigPmeoEOgOeZLTwVWI6xulvL+tnxP0jOYgJICLyHH/2c0FGTc3W145DJ9rGT2K5vZL9pqzcwlENiXTLNgy8+78pv/+u/d4ELE79W/D390OUigkgIg38eHfDz0or6rIv5LDTA7PQQyxyO4zc983NwPd3tNTUAQAs+1X76ye/o3uV20ztq/s1iU4LzMEx+bZtlC0C5gxyO4q8MWXlFlz57h+o2VjidiiZVa0Fpr6vbdloFJjwOtBQZW9MlN8Skysb57sXRwaP/TDP7RBM8WMC6PzglJbH8f497bz5+JfgONvKJtKLCSAi8pyR8x3sjDfL8X7z1kb8sbwcHxe+hG+KnnImpjwxeUV522TfvG+B2QOBBT+0Tps5QHuh62cBmxarzo6f3yUmddvP+lCZp1Ip/KDHh2dc5UGB1fg637aNt44DvvuH21HkjY3VDQCAc4LTXY4ki4FXAkPuB2o2JkyM/65SdrbLfwNGPgEMe9Cp6CjfvX2i2xGk9fnk1W6HYIofa20/UfCZo+s7MzjL0fURZRJyOwAirwvLAEf/ymN/fXsiSsrrUFLsdiS556r+kwAAgwrTzAw3Gi84Glafl+GnrFbTr745AgSNh0OUN+rKAQAyGm79qan1ARRWklporHEkNMpX2fpeMVqsf5Ief0QOxgnBBdkXNCrn+0NS3t+4pZtdjoPIGqwBRESeY+VpVdb2/VnOW0rKvdccLdekTbDadHKd66eplDsq61o7Jffb9dV4XiiRmxKPH9mOJT5K5HiVF/pRskKuvA+ibJgAIqKctAsqcG5gqtth5J7Fw4DKNZYVt68oxXEBi/vP0XBCr6dW36mB2WaicVc0Akz/BIhkqBVFujU0R7IvZNLWRgu+s5mfmy/DgMr6dCPq6by42rgAKBlvSTyURzYvA5aPSpigfbsrq2nQvh4Ls7LdxXrLyiLjfJZnJzKMCSCiLNgBtPOsOAh/FnoK7xa+CkSaLSiNWnxxNfDOSZYV92vRA5aVpYeW33V8iU8LX7Q3GDvN/AwY/C/gj35uR5IzvpleigMfH44Vm7a6HUp2P94JVLtxcalhL54tUfv2CcDHF1oTDuWPfkcDA/7S+lxHDZ+TXhiVfSEbjC6639aRwHgWm1lnUak8YG0wyhNMABFpwCSQ/3TFpozzv5leilXltb48M9raGMbrvy5FOOLSyBs+HrVHz9f96R8ldoXhnPqK2N8t7saRQ0bEOqlfWuaDBBAARF1IgvNCinyoOZK63Tq3HQ+c4u+OoP2sAF6oIct9JjmHnUAT6cIKon5w7fuT8HGWZf7z9Wx0al+A/Tt3cCIkS700fBE+/WMV9tqxPS49cne3w/ElLb/kqSVMmlBbrSPJkSapnUD7rUMjIges3FTrdgiGCZ/vDeNNwpmCoXzBGkBE5Dl7iQ3oiK04MTDP0OsnLCtveSzWTEoZkrhVZV2zL6/i6pqU/keawi7VALLIwaIk+0Kl9gx7rXai1wWbcbhYZss6KVcoW49wMJHhtwusTjWL00xN+NXVbgZWTWh9XrEKWOvxIe7JnzYaO48AgLMCMy0MJDMh7etXzPaRbH1e429vsQ4Aa/tT/mANIKIskg+cPDg44f6Cb3BqcA6OCSwxXVbhgD8D2+4K/CfdBYk/ef1SUEqJ5ohEYSjzPYahRY9kKkX58/6ZRiJQnZPts5tY/C8AQLeGgQbWS/kgGtu8Al7/IbrolKl3JTxL80F9eB5QvrT1+euHKX97+bd5KXnUJxdnnJ0pd/GnQImxFxpwTNnXlpaXaFDkNJwUnG9b+X5XKOzv1J/IS1gDiEgD2++eUBv7xu7IWGLrBvV5Ps7peXXI0o8mlGD/x4bpG1HFYZGoNz878r5Ri8oAsCWTKYnJHyJCoMbCc54UQ6PH21Y2AMic2RfyvIDyAxNARBqwWqjzmh2uoOjH85cHv53rdghp/ThbOZFdW1HvciRtZfol83dOetjdLMvJJmaO8HkzEaIkFv8+V2yus7S8RHb/8gR/2qY1NLMWEjmHCSCiLJIvCnPshNzDmhG0tsCSCdZcgDTVAuuc6xcgb21a5HYERJkZPRysn+PoSHp2Di/dRk2aIefjF8q1ZelfU7u59XH5cpeGrSfPqq+0tLjXvhyKbg8NsbRMr2Mtdm2s31VKHCsWQksKLsxayeQgJoCIsuBh0x1haTwBtK8obTvx4wuAmQNUX6P50PvN34H+p7s6FPryTf4YftrU6czEN6wKo0Xf35bi6Z8XqM7nSTLpYXhrefcU4LPL9K3LxKb5y4L0neA7J0vwaya1Pn7jKKDPgfaGQ/7yyUWWFnfPomuSnkvpjcEUtkeNbWXn87HtyKd+0bG0tUmYiwKTMKjoaVwVHOP4uokyYQKIiHLO9lBJkFSsbDtN73nR2mnK33CjzhdaZ8bqStfWrYVXTzX7jFzScpctXYw52QSMzW5sY6qJlsERr8ZGDtX9mnWV3uqLa/NW9/ad5EMb7GnqvP9jwzBw8mpbyjainWhyO4ScVFHXrHlZq89d9hRK8r2byNAPJZELmAAiyoKXTzmOX3DuYdKDHODVRKfXPTtkodshEKEpHMUj3xtPLnml5pAWdh8Rc6cTaPfwIyQnMQFERJ5kpsry/oFS3bU5zB58pZR4YdgiLN1oXzVuMqG+ErtgS8vTIqH9rqCv2dGRsMV9crjl62lrcN5rY/W9qKkO5wSmoT0aEND72ZYvB8La7/JvqLKhE/WyRfYlSNXeW8rntF9gbfayNi2xICDyhIZqoCpNs2wjqkqV8kzaEa1NuBN/DV2wue3CKuavS4hj02Igai4hdEFgsqnXZ2J3EzCvdALdFI5i4rLk77AzKrQXoLJvNPv2OqnVSidyCRNARBr8Gj0aAFAmO7ZMWxjdw61wKItnCz5ESDh7d27z1ia88/ty9HzfvpM4v/FURZy+R2By8d0IQRlp4y/B8S4H5BA7voTXD7e+TBf895s5WLRBZ8L20z/jvcI+eKrgY325tdpypX+bIfdpfsnlb/+hLzYVZTWNePyHeQivGAe8dRww9X1Lym3j53s0LXZn6KfsC715jLlYyDveOQl49RBrynr1EKD/aaaLmV58R8vjusbWmwETi/+luYytjbFRm9bNAt48FpjwmqmYAl7JovjYi8MXoef7kzF7TWXLtCnFd2l+fW1T+htDZtNn14RGmyyByFpMABFlISHwWvgvOLrhbWzC9i3TL216Goc1vNfyfGD4DDfCIwPSjYpj1amXoyPueJQnR6+uV+4CxhNAZEJDpdsRuKd0CgDgwsAk1YuCr6etwcL1KbUUGmM1DkrG2Rebip9mrcVnk1Zh+eI5yoT1s+xZ0XK1ixwv7hDIMZUW97OzZYWlxV3d3+RNm6o1yl+D/Xo5Iz9+g8vKlJo2W+qM9ae0Zau1NYPz41MnP2ICiCgLAQmJAMrRMWl6IwpRjW1anteindOhkQcx/5NeUziKB76ZjQ1V3uqQlii1yYBmKmf3//1mDs5/PSXRY3LHYMWFBPdNRJQXuK8jyogJICLypJCwoaZGXbnqLLMXWE7XemmHBnRAnbMrTdRUm3F2Z1QgVFfW8nzUojIMmlaKJ36cp30dLl+xCt6/866aja3bR425EVaMNNtsJ5oQTB0JsHYz0FyPHWC+j5J0dkaFoZHqOovK5AmRsDUBtcGrLsqgZkPrcWPrJiDqbm1My4+fzLD6nlBphpc6dUdUIQBruxnIdg4ZjUrWMCfLMAFEZBG7O9nLN12FwbvymUz/2PoyXTK26B7MLb7FvQB676c6q0A2YUrxXTj8q2MTTvJTTly2lrV5XRvTPjAYnPpJkp5fqcyFC1pPtsczacsK4JX9gQmvA8t+A145AFg01PEw/jT8L61PImGg9z7As7tiRvHtKEBKkiX+PRg8ge9QuQhTi+/CKUEdCdSY74uexCmBORAyFtOcLw3FkJXae8vFbZC0aUzoY+uVA5TjxtYy4OV9gVFPuxcXYMHxMweOD5Tk9uDgrMt0Qg2mF9+Bh0JfZF1WV8I+y6L7PjoU573mfBNiyk1MABFZxMidWSKjdhb21DLQrFm9BlChbK0Z0dSsUtugbkv66YlW6hyhidrKxTuG8T5Flv8GrJ2hPF47zfEwtqlYBACIRCWWbKhMmleE9H1QVNUb62Nimxpz/Z4cKlaaHqXIOCaA8lZjSifrzbVKTTkAWDzcVNG1jWEc/9xvmLRCvWavFpaduzHR6TqzX8G+gXXpy0143Eko/QydE3D2mBOVwGKOMksWMZwAEkLsIoSYGXv8gRBiohDiMetCIyKyR7prYr2ngK/8sgRVdW0v5nLwclu3xJMltSrVCBY4FEEyfj+5yr2Lrz4jF+OiN5JHlQuobGnVBhNA/ri45K+LNBCxSw9pLiG5cH01NlQ3oPeIxa0TczHhTXmBmy45yUwNoJcBtBNC/AVAUEp5IoAuQgj1dgFERD4USm3OAeCLKavx/LCFLc+dvDxLql3Q3ACEG5Wzh4ZqZ/tViK8rGgXC6Ws8pJ7UtFzHBkIaVmD0U+WZVN6IZBntJdxoruZLuCnz65vrMaOkAkVITexI9B+7POFp5m1yzZY6RKLqy5RW1GsINrNA1NoRbtoIs4N3TZrz+3Mq3RKrxZApASQl0LhVU39VSf2i6LyKLkAYBYb7G/RDUpbcIBBFYZtjAnlOpNnGPvG8zVACSAhxJoBaABsAnA5gUGzWKAAnWxIZkUcskHu5HQI5INOp3LLiv7U+adza8jCc4YLNTouLb2x98uwuwDOdgY/OB17YQ3lsl1V/JD/vf7ry99u/A8/s3DI56bNUOyG3tQaQuqMCSzUvy06gfWDsS+rzImHl9zDi4azFhCMqF6PP7Ax8/bf08wDg2V3Rs/r9Nv2JBBHFc0MXoaE5+8Xlmi11OOWl0egzcrHqMkPnbcxaTjb7zXzWdBkZNVSln75spL3r9ZPFw5R9drzpYh7q+uXZyoNMCaDxfYDnd1f+qbCiUtzS4r9hfNG/zRdEnmJ1/316S+sV+gRLim9QrQlKHvH0TsA7+Zm20J0AEkIUAngCwEOxSdsAWBt7XA1gF5XX3SqEmCaEmLZp0yYjsRK54pnm690Ogbwk3Hon3lNVdlfHkjNR5W7GJf3G483Ryyxex8Tk5xvmKH/nf2egMHeSK3oSQOwE2kfSvc94jRcNnb9/NmmV+syFmTsGvbj2mzbT4if+9U2RpPjSNYnctFXpM+uHmevQ7aEh+G5GaZtlzA4ykOn1UkqMWVyGqEsJ7byy7Ffl79rp7sbhCcr2Fo1KTI714xOJP54Tu6+coVZZ+uOve9vwiPnmRiP0iuubHsq+EGV0XVD5nQeE9tqn3Pu6ZNPC7MvkICM1gB4C8KaUsjL2fCuAdrHH26qVKaXsL6XsIaXssfPOO6dbhMiTmhF0OwQi3eaUViX3jeCA+Amwl09k8q6zdk9lKb2rpsHaauDxBFBjOPsFQDw1s7ZSSS5/NXWNpbFk89Psdbjxo6n4fHKGJBhZg7/HVrEaQB9NLMFV/Sfht4Ub8e7Y5biq/yTUNhlsluXi55srx5Zx0cPcDsE0r9Te9UYURG0ZSQCdDeAuIcQYAEcAuBitzb4OB1BiRWBEXsHh3XOPnadpMpdP8LO8t9s+m46ahmYEEmpjxGvRpL60OaLhBD9faq+QvTT8JrVsaWU12vtuCUC5uG3ZhDPEIDRs53buVdZVKu/Lin6GiDSLJYBWbFKaVa+rrMeyMuWxapPMBO4fHnL4WO9z3qm9qz0OabJTdCI9dCeApJSnSilPl1KeDmAWlCTQ9UKIPgCuBDDEygCJ/OL4wAK3QyAbPBQa6HYIrT77C/Dsbu6se+oHwKin207v1bHlYUlxT7QbcDHOqP+lZVrBV1e3PL4pOAzvLj8LaNyKNVvqbA3XCl65i2jIJxcDz+9pfblf9LS+TL3iyZSVY1unje2tbIvxf1VrYfr+62eXtT7u1RFXPTdA80snF9/dEqqUEmOXbk67nJQSH01Y2WZ622STuffyYMGXyROWj2ot2YrNfNLbFhSioldHoG6LfeU7yisXpg7JlHytXA2gdfsz+snIDM/stGBddcqafXy8yEWbFiednzjllMAcBNVGPyXyCDOjgCGWCKqG0hH0JABnSClVegEkyk0nNbyOixqfwaGBkqzLntH4iv0BkaVuD/2sOs/xu0zLfwOaXUqcTHlP02Kh0j9wbv3QlueBlb+3PL45OFx5ULsJ7QqyH36ajfZJksu1sLRaORZotOFwvNgn93jKFsD0xWBCkgQAjg4sMVTM19NL8fiP89LOm7+uGj/OWtdm+rHP/mZoXZot+BEA8O8vZ+KFYYsAJH9aM1ZXoNtDQzB/nbZtqG5sP6sjTFaZY83TVLJuNQ35N3JQPNGuf7ed5jNkEzCKW/1H9mVscFFgkivrJdLDVAIoTkpZIaUcJKXMjR7QiBJkO6ivxc6YJ/fWVNZK6VLtDcqq1+AF6PXTfMOv19KMw9d0VE9WuxOa+EsqCGY//IyY5+whJfW37p1q5GQ3LT9fIxd4EhIbqxpafhOpZTSnaeriyFYXu1BOl3wCWvvzGrskfc2lVDVNNkedK0ndDO9jwrLNOLTXLxi3NIcGStHww/LroZM1frxHZHjmXAwy7eNscmQPRz5hSQKIiMjvFq6vxscTS0yXk7MHcUvbp0uENdTuydnP0hW8WDHL6JC+EuoXAlpLtOO3MGiadZ1NS79exbum7ec1eaXSzG1AphHpcsz/vdpaQ9Sa/vOcP2psqG6Irdm7v4GT9t3R7RCcx30SkSomgIgorxmt5TGt+A50r5vT8jznTzV0JIDaXOx+dAGOmnhn6wnysIew6wdHWRicdl4+SbeXTRdGvToCo59X/kY92ollpBH49NKkSfVLRqOkuCd2wRbsinLcPbZHcp9CabxYoK0ZZFxJcU+0n95fd+WVTzZchntCyUPLW7/dSgR/vAPDCluHfDZzAR7l6aQ+Q+4Dnttd+d38qPQXtTbWCfeI+RvdjMxaWbapX6ouwTbNFcqiVqzC4Zpi1Z9ei12H3eLoOo3aJO3rD8ebzd/cP9b/K/SD5mVzpZKjH1Vszr8GTDxiE1FeaWiOWDZS13EVPukPxRImPrNVE7DL+oT+VJaOMB+OQXpOVH3dCbSTfn9B+SsNDt1sl8Tf+YrRSbOWDH4VANAjsATHBhYrE6d/bHkIHcc+oTvJ3E7W457Qd0nT7EhcXh4ch4MCq1vXYeInLnk6qUlS5/dNyohXmPkZpJT4dkapO0G5bNeGFW2mZdtPvz1mOS5/e6JdIWkiILHdip+TnnuVgMAljc+ozv88fJaD0diPyRTSY92SGW6H4DgesYkor5z0QnLHrrzI18iCJmBeqH3jfgRuyd93nk59s3PJqsSLEaMXidZfz7TdHsysI8rtK6tlZTWq/ft8P3Otw9E4REsfQAa2vLdGL1OZwyt/Neuh3gzs0fDfTZXthWM70NoX48cTS/Dfb+dkWdpjuOm6xsvJW7swAUREeaW8tsntEPzJgltqekswflKpviY9MbATaL/L9P2JtkvYdNtYonVb9sZlEqD1l/Di8EVo0JAss78GkH9/i1JKlNU0oLYxArX3sWhDjbNBeVDiz8/ovv/raauzL2QTryRB0rG7O5z65gimlmyxdyU6jFu62bXvw47zFiKrMQFERHllctGdEEuG2VZ+rlY9lhbUAOoe0Ne3xSVBd4ZxzVU3fzwV578+zngBqydbF4wZKc250vr8r8BzXZKnvdgdKBkPADi+Qfkc3irsi76FsSHM538HRJoR/vxqyF+esCzc+yYcg7FF9wIAdhPJF0mJ+4sHQl/ivYKX05bh+MVMQlxaOiVmJ9DqPhi/Esc++xtWbq5VXeacVX0cjMhBGg6IMl0yNotzMRHji/6FAKJJr3v8R+MjeeqV+pv0cy2CopC5y8G6pjCueMdbx2sprd0n9Sl4C/8LfZR1uatCYyxdL5EdmAAioryyi6hEYORjLc9Zy0ObqI4OfuubPdoZsE651TxQYtSiMixcX228iLEvWReOGRNeN/a6+i3A6OfxQ4bmNr9Nn4/Q0mEQEw2uw4Q7Qz/hnGD6vgicSACpXatrG7HP3vi+mmrdiGVO+32J0uxr9ZY61U/pmI2DnAvIQVpGmhNC/zH4SbyLrmIztkFDclk8nreolu01L2s2f2v33mn4vA0YNne9zWvJ7C/B8bghNNLGNXDbJecwAUREZFA+nWwKM6OAeUgupXS8JqIhUeA6GcWbqv2HAI98N9e5UKTEf7+erW1Zm2PJuG4NK7f7N//jrHW2lk/2eGXkUs3LJg7OkHV78uCO3GtNwN4NX6R5Wa/XXL59wHTc8bm+jnqtfEte+27Jah7/AdiACSAiIgvkfAuIaLPbEZApFmygWa4SfJEAgszYFMfJ5GU4KrEiQyy28voVH+WNxQb6P1Lbm+X6Ydgu/3fIrqZe78W9iZVJGyeOC9wlk5OYACKivGZ1Mx+rhphvo9K9zi0BQIQbsi8Uo7evH8ttVr/rrPXbuTU4mM0DdXLi89q8tdFcAav/wHehR1RnO3kBGfrgbHQX6/Fk6BN8V5itzyEHmoCZ+v7s/u79+1v8R/nLuDwwFlIC14TU+68qKe6Je0LfKE9+eQyY0NehCO2j5cK5pFxJgurpBLoYCfsBPTWHLPT3UHJfgl6r+aonmleuONzUurySeBMAtkMtfix8DN3cPg8hb5v3XZtJq8vrUG72HMMnQm4HQJSvPgmfY3N7YtLCNxf5E/tZXuSSjTX4ffEm7NShEJcesXvLEKppRXw0etqoZ1RnZTpRTTyBf6TgC3wa+bOFQbljS10TdkDujH53z5ezMMBkGYcFVqrOc/IiTqybjntCRfhzcGLWZa1vgqD9ffpmH+lRp9b9glMLgddxS9Zl7wl9h9fCfwUmvqFMOOlfNkfnTyHkRj9z9hK4rulhdMLWzMd2AIWhAP7RdB+inknlGHdOYDoOD6zAn4T6fp4I39zUZtKpvUejMBjAkmfPdyEgZzEBROSSJ8M3MQHkQeFIFKGgBytHBgssL/L818e1NNvZZbtinLjPTuoLR/KvCVgudAK9ZMNWHA9gyUYTnT9rZFvttwRV9fZuh07fxQ8hrGk5J6Iy8/UJm7/7XEhBfTl1Nf7tdhAO05O4tCLR6GYtHK/1EyMhMD56KADgVA3Lj4z2sDcghynfhzXbgyOd8Nu+BlJTVt2Ag2OPmyL5kVz24FUOEZF7bvtsuo6lHTxkB6zP1yf22bK1IfOFqNeqt2eU4W5npvfhiy5sXJX7H5DTfXkVIKJpOa9dXKayPb4c2PTWV2lvRpsr9Bw3EnOIRo83bv5KvHaMTIzG23sPa8VHlfP6PrMNdgJkyNrKesxfV2WqjHfHrrAoGv9gAoiI8k+G4+xvi8pMlWPbITxYaFfJAHLi+kqTXUWFK+udt7YKE5Zttm8FteXAt7cAjVuTp8fOgU9YPwDHiEX2rR/OnL/+p+ZFW8s/ITDf1vJT/V9QPeH8QOhLfFjwEs4MzEAXUe5gVMlUv1cpgSH3AwOvxl7Ny22NwWsX15pVlbY8LCnuqeklD4S+bHlcVp0/SSOj37BXtowzAzPdDkFVx3bW1yD2ugKhLbnuFU7UoM1FJ70wChf2He92GL7DBBCRi/7ZdLfbIeS9dM18+o3SOnStkzWAgs6tiyx30Rvjce37k+1bwdiXgLlfAzM/U13k66Kn7Fu/Q05rGmtr+b0L+ttavh53hn7CmcFZ+LDwZTwd+tDawq3YddWsB6a+DywZln3ZfPXzfbpfcmfop5bHxz73m5XR+IbR2htuJgpDwltNRyIJl3jPXPYnFyPxP98moPNIdUP+dVNgBhNARC4aHD0Rf270/0WZ3yT2I5Ku34GXf1miu0z7b974rDqziyL5eK7mgbuHUlp/AVTd0IxJK9yr/ZJPvHwH2red0zJxr5mRza/tS7y7Dbtpu+L8qwFE+WXQ1DWGX5uPCT4mgIgo79Q0aut41VOEvbtrD1/76bYlR0a80if+BSZfKDt52WzHNnTX5zNwdf9Jtnf+7HVOfI/6vz4Hty4bkouOsHm/nUsSb8ZovSDzaVrQEfl4UWsXdgJNuYZHJiKX+a6juhxxe/AnHChWp53ndEewmiz62e0IfMNLv6lB09bg9yWbnFuhlo13/GvAhnmWr9qOE9iF62sAAI3N/urPwWpu9mfhhZpB3bHO7RCMMXkwOVostigQd1wVHJN1GSv31t7Z85NbOqPS8jKHFT3cZlr3wEbL10PkFCaAiFzmpYvVfPJQwZcYXPio9QXrvFb6dnop7v1qVvYF12tYJg2zoyP4kWv9R6S5UH7gmzm44cMp5so1uG5Vvz4JvHuKHUFYXmIwdpYS8UASIrdY8Hk6mCl/PvCWY+uylMkaQN8W/c+iQNxxb8G3hl5XrzHhK2HN6GG5KB/PLIUAHij4yu0wDOEhjpzEBBAR5S0r76obPXbf//VsfD9zrWVxpKqsy++mM37R7aEheHP0MgtK0njab6BJTbZt3I6aIoFYkiHKk2PbqX19JeV1aadvqmm0MZq2lpVtzb6Q1wj2AaRV4vZXVe/DZtpEpvAgZ4aZ0498TBwzAUTksvzb7eQOJw4akahElFe/Ohm792m6Np7JBEjvER5v7pHl/dmxlbYkgPgbsFS6zu/VfDO9NG3y5bK3JlgZUlYNfmwGyD6AHJWPF3Jq+FkQkRoemYiIUmi9jreywkM0KjFvbdvmWuc+2h8fv/WcdSuK8UK/Hl5j/oTZzc80/bpT31Mh7KsRJjYtsrzMYCBeA0gCG+dbXn6+ErMGtpmWKSm0sbqhzbTGsLPbuy8vaJeOdDsCX9KTip+bcNzMx2ZPavhZ2O+CwCRcEpiAg0WJ6bL0JOXJpOb6ttO2luGW4BDky215JoCIssh20nnrqXtjyqNnGS6ffQDlFqOHjnfGLsdFb4zH9FUVSdN/LXoAN29+yXxgKdZXpV7Q5c5Bz6p3EpHSP7UO4gm9LP2y3BwcZngVFVlGV+vwydmGy1YTy/8gEpXA2ydaXj5pk5ovXrHJ+eZYRRUeryGXTmP+9cHmhpdHLEY44tOR4mwSTXNu+U74IhcicY7TTd7fKuyLvoVvYmjRI46ul9rSlUAb16fttO/+gccKPschYpV1QXkYE0BEJm1bFELnDsUmSmACKBeYrVEzf101AGBtZZo7EzaI5nQNIGt+U03hKA58fLj2F3jwM01NMLcTmZM4mVS6MBR7ILEGEHnGZW9NdPzmhYiyXxhKr9/oZRg8Z50/a4nZJIy2/U+9EO6Z00mgDWlqKvoGN13nNNUmPRUA0KAk60PIj+MME0BElHeERReT6S5/mM7zgLz8EtSagKn7dYH3h7GNx8/8j/30fMZVLiQDKX8Y+bn/trAsP3f9KlITQKfuv7NLkdhDSokNKTWZHRyYkHJOfm08TAARZWH3XU5e1zivKzbYVja/T/d1blpjSTn7iVKcE5im4xUe+PZTzoDbNZWrLnrLp3reG1zNwmza6uyIU/lH4ujywUDFKmDOIASiYVwb/BUBRGNzPbBtk79s1jaq4RFiGc4LTMG+Zb+0TDNy1vXznPUGXpW7mhFKen7DCXu5FIk9Bk5ZjeOf/y2p70ThwEX8NcFRqvM6o0J1HulUXwnM/NyRVZ0VmOHIerwklH0RItLi18iRODs4U3X+C81Xp53OPoD8y8pLotaaDs5caOVyjYqARd/MyKIH9L3Agx/qoaVtO/v1o/sHzcYfbgeRw04ILMBfSl8EXn8RAHBW57+iR8E3AIDPI619O/2xvBx77dgegPPpTicu7shC/Y7WtNh/Cr5WHiwERh34S+aFs2ATsFa/Rw5Leu7Bw5Mm6TqgB4BJK7YAAJZv2oo/7d7RsXhuCw1RnfdZ4fOGy1X7evJ2BMwf7wIW/Qzsdhiw66FZF9e3fScvfFNoBICjAORPPSAmgIgM2GnbImyO3ZG+7MjdAQC/Rw/PmAB6J3KxI7GRc9KdbBpN4AiX6y779eSQYhz4At3cROr90hm3T7VH8kXWts1KzbEOqEuafs17k7BNYdu+RRyRL2fmeSwgzf7OeSADgL81PYi1SG7y5cdPJhKVOO6539LO8+LuYFexxcSr039DZ/X5Hesc6hvSU2piNfWbHerXKc/aDzIBRJRFuov8xP3EHjvE74Ya23mwBlBu8OPJFVnN2FZgTa2veBm5uT/JzXflfen6YKptikAIQEp+K5lEo5L9LOgkwEQvtdLS+b+Xbl6lNrvTQ+19rNxcm35G3lD/gpeVOT8aZa7gsYnIACsPOB46duW9Y8VC7ALlDs62qMMVwTG2rm/Jxhpby6c8lPUuVuse5wihrY8Oym1G+63oIjZbHEluGb24zLKyHvhmNgbPXmdZeV4Vb75r9LyIKUlFuhuLTjUvt1Km77MAzXgoNBD7LPvIuVoiGeyCLdhJVBt+ffGSn72VzXJT1VpgbayPQpXPpKahGWf3+b3lueZPrrkemPpB2+lrp+uL0eeYACKyyCn77ZRx/qn75dYIDLloUNHTLf2+9Cl4G70L+md5hbmDdf+xK0y9nqxluv8Igydv1lQA0l/ID0VPWLBiZ7jdRDKXDS960NDrfi56zOJIMvPbJtDQHLWsrEHTSvHPL9SbmOcKEVU+M61ftc82CVflWmrhgs0f4fbQzzh0fm9g5OMA3N1HjDC4H43rOOoBYOFPFkXjc28el3H29zNLcWgvg/2F/fI4EFEfVCJf+hFjAoiyuqDxObdD8Jx0B5nCYOafU//r03eIyCZg3rKdUPq86Ca0jRT26PdzMWtNZctzs3cuK2qbDJZA7vPCiYN9+xPuq3LTDiJ7NXovbNl+u9z3W8LKCwImm4Dly8WbEblWuaRTc0INu0prRv40o5OwoKlWnfqonXmlKbF2fNsN9+fZJkb8q15r/LU5hAkgIotkGya3KMSfW64JR6L4fPJqXPveJEMnV4nXB+HYnc9egxe0TPtt4UaTEZIeTHB4F78ZZ3nzt+CvK9hHv5/rdgi+YzaBwwSQwpu/X/1Sv82mcGutuqhIOKeOZVtz411TkjQn1+mS65rPwQPs/hhgAojIQlkOPSq3A3PlQO1XageN3TSM5nBg4xwIWFPNf+jc5BpH45duxt8/mWZJ2VpkPHYuyI9qyTsKk30yGW0CZm6tukrZWxi/c8ZLq9x1V+jHjPOXbqzBWpdHovHbMPAVdc1uh+A7s1brG0WpR2AxCtH6ORcL1qBV5/89+IvDFykPqkqxc1Np64yGKgBAXb37fQGRBzXVAWumAOtmAs11GRfNlyQyE0BEKpZGleHdV8vOtq7H77saudvhbodgiw4i+8VOp8gW3BocYsv6y2vV2yg7btD1bkfgC9lqAdq78ti6s7Q7uTg4yfAqOjZZ16ktectRgcwdgj8zZCFOemGUQ9Go8VcCiPTbVKVcnGndk35U2BtPhj5tef5iwXs2RJUbVO9PHHiRFaVbUEZ2H4xfqTx49RB0q2+tLY1VEwAAf2/6zJE4yEnJ25aUEr8u1Hku8uNdwAfnAP1PB5b9al1oPsYEEJGKAZGzsXfDAGzC9pqWj9fk+SlyQtr5udqJqfjHGOzT8Bn2a/gUEyMHux2O47rrrFHR0BxBfROHus1FMuqFdK59+5niaPa+YkYvsiZJVN3QjIe/m4O62G/Fa7vP+5tuTzt9v4ZPcUDDx/gucrLDEeUDL/y+yE7x37men/uBgdUtjw8VK60NyCINssDtEHDArh0AAO0Lgq0TAyHgqgEuRZSd3kq1B4jS7AuRv6RsBKu3pK/Bk/EG3IY5VkaUE5gAIlIhAUQN/ESiGU5dfv5n24sC3zcBCwSwd+eOaEYIER/uUqy6sMxW+6OsugHPDV2IPz05Agc9MdzSdadao3KAJLtlP1uNpEkS+WV43qjMvsHe9PFUS9b19pjl+GLKGqyvilfp99Z+shnp+xFoRgiNKESz9Hk/Ay19anhn2/TWFkCkndPnRul+tXvvvC0WP3Me9ttl29aJImDRiYhSxvvjVmBuaZUF5eUr7uXaSt6aDd1nE/67NrEbPxEiFXbshv+0e8ek5/16HmnDWpw38r7TsHundp66WNAqICPYz8Rdo70D2moAPfjtHPQfuwJhB2qJnPLSaNvXQW1JAOHGejz10Q9YsK467TLNEeuGhk7SaLD/oi0a75hvnI/G5ux9mhwmlhtKaJVW1KHbQ0Pw8YSV+H5mKaKeqE1lnB/3hYnaNVdmnO/KZYrXqoFlsR2y15jztIZqoKLE0VWeGpiDoM6RwBJ/a37/3dmtKBRMrlCR8KS4IICCoLHf2N5iPYrQhGeGLMTF/cabjLJVuhtrvUcsSr9w5eoc+Pb9/w6stqws+dxG9xa6YS4TQGnwEyEywKrT0DMO6Ixvbj/RotLcNyZ6hNsh6HZ1zScYWfQA9hbrDL3+2MBiFKK140m1a9/mCA/suU5Go6j95g48seoGPPblOGdXvuAH5a/ei+S+R2RfpnQ68PaJ2EVUZl30p6LHgdX6+xlatF45yes1eAHu/Wp2mw6Hu2JDupe5JtuveUL0EEfisEu3muluh+B7vxY94HYI5rx/NvC6s338PVfwAe4Pfa3rNSLpMY+zRi16+nw8cO6Bhl57cGAV+hS8ZXFE6b05enn6Ga8d6vsa9U1hbr+pHv/BxGiKC38G3jkZ2KSSNMxjTABRVhIChzR84HYYOWmbohDaF/m8qUCCzyLnuB2Cbvs3LwQAdNZwcaumAGFDr/PSqDY+aYXkee3XTgQAFEvto5F4/aOvXLdU1/KyYhX6j12OMYu19weUabhfAOgk09eo8pIDGz5qefxjlH0A5TszxxRP2LzYldUeKTJ3SE7m2FWR7sTAgqTnBzw2DP3HqiRrbOL3BNDMNZVuh+B5urZfl/ZhfsAEEGlSi3Zuh+B5xg88/j5g+Z+1n3+8yvLq8jr2xZNnJKQHmqlYv/4nf5qn+zXPDV2EGz/S3h9QarMxr7cAS7e/b0ARdu+UH8dKr38/5J7qhuY2CVw9hNC3cSU3ASNAz/mofT/kxnAUzw01V/OCN6ZIq/Tbiv49Qr7UImQCiMhlrl8vEgBzO30BtDmPOrX3aJzy0mj0GbnEVFx24YmV9dRGAdsFWyCgXBCl+9x1fxfhRmDrpvTzasuASPa+evRwY3Sz1IRQwGMnZWoXWLm3P2/7uXdAHbaF88ntYEMF0OTweqUEqtY6u06fO6zXL7jZos7g9dgZlQgZrI1LDmmqBeq2uB0F5ZBdsAVdsDn9zNw7IFuGCSAii+i5PFkZ3aX1SQ7toPxY/VZa8PlfgrGq8/r+pt58xktffbZRzEinWAKjCzZjcvHd+HfoO2WyFZ/zoBuAl/dNP++3p4Af7zK/jgTx5JVWUprv6DqSkgC6ril9vyAb5PaYFd3H9Pr0WiU744/IwY6v1wvmFt+CecW3OL7eroOvBt52uM+8Ke8Brx6sdCRKmo1fpnJBZguJ9mjA1OI7EdRZe8gpo6LeGfAj6TzNpjtBp/dWGYii3zHAS91tWScAnBWcaVvZ5I5AyvlHctcJEpOL78bE4n8hFEnuN5AyYwKIyCoaj6PHNLyJi5qeM726B5r/YboMAqSGoa2zOUJ4s5YPOUtCoinW2Xc8gbGrUO52nhqYAwCYtabSfNPAJcMyz1842Fz5KfTWvtGz9MDJq9HtoSGoqk+utZR6XXJy7PNLdEzDWzi7sTeuanq8zbyXmq/UEYV+8+TeuLH5ARzf8Iat63Gfh7LUAFChcdQ6q5TEkvtbVji7XgctK9uK0gr/NlcWALaB9j7XnHZ+4/O4v/kOt8No4UQTl5Jyle2pmrXpSJ9MN5YTt+VQJN0+gE3A1ORO77NEHpFtd7MJ26dMMZaH3Sh3MPQ6u3ipNosR5pqAtb62odmmYb7J86QEquqbsY0Ayrc2Jc+L7Rl6vjcZADDz8XOw/TaFsXnun3DMW1uFLbVNOHX/ndvM0/vbaGrOPozzj7PWQgiBT/8oAQCsq0w+eYumZIDSnQRuQifV8jc4sH9sRCE2YEfb1+Mu97dNstfZfX4HAJS8cKHLkShy7QJsrdwRTShwdJ1e6AOI9PP7ebQdUvcHiZ9R0s0pfna6sAYQkYpMJyHpdtLxpkR6T14KQ7nzM/RjEzCrQrb6NKq63lw/LgUIGx6djAxKSFqIlr/pt4xRi7SPkOWEi94Yj799OCXtvIDOZhWzlq7G9qhGAFFEEvoPWlq6seX5f76chvu/mIqN1UriJ3WfarZlgi/3RR7UXjS6HYK7nO5zKI2a6krnV2pxP2J6tIO+bU7ZxzKRoZXj+8ZoBGhWaZ4jpdIvkIp0x4HcPq/Jg+NWUy0Q1X6jtAPqEQk347NJq9AcSW0O1rqBBCKNQCRh24iEgUjyjThqlTtXnkRuix2pilITOnva02eBG6c7pXIn1XmvX32Ec4HYwNxdR+u/jcd/nG/4tX8JjMXUojuwoOimtPP7jFyC/3wz23D5pEa2nFzn0uXIFcHfdS1/4tKXMLP4dnxQ0LulacmCmROw3/v7457HHgMAzCm6BTOKbkNFnXKhmXqir6UGUKLZ0b11xWilRtl6dz/X7uDeHfoRlwQmuh2GOxqqgeW/xZ6498V26LMXugqVTt/t8u5pzq4vwWGBldgvoK+pkJd/ds353tji21uAZ3dNnlZVqvwd3wd4rov6oAZpzCv6u4XBeU0unTmk0VSrfN+/9dL8kncKX0NV35Px+A/z8N645Ka4ib/7myZfCHxxdeuEz/8KjH7WXLw5jAkgIgMy3Z3uusM2yROuHQTcOSlDaV4+dUl2YaN630VH7+WtJmla5WJNgTODM9FJ1KJApG+K0/e3pZiykiNxWO3DhJOTbAnFxLnW98Np7TZ9XMDYUL5nBGdjwrJyAMCmpcqoQKcHlcRjO9GEDkK900a9CaBrmx7BOY0vaV7eSic0voFTG18FkNpBZW44PTjL7RDc0VDpdgQt9hQbnV1hmfEbEE4TkJ5tNjYwfCbqUex2GEmSktRODAc6/7u20ypWKX/nxebVrNdcXJFwr3YamdRYo/yd9UXLpCvemYjBs9dlfNkO1co5yEvDF6O2qbWWT2oH0Vg2svXxCpWOyLPIvSN4ekwAEanQewERP4y2OREp6gB0PqjN8lf12CP2AmO7GzcSF1XY1vF12q3Rgj57tHwT6fp5sau2gJGTYQ4Lb17/cStafpd1jWFMLWlNsqX+XlOHObeSl77KR75XRk/6aVb8BD99dKm/Bb0jz29FeyyVXVueO/kZbMF2WC2VkR23Lcq9u/1e2p6c5Z1LAa8mOLzAO99SW4vkHm6H4HHxby/99u2F/vGc5eWt2QIinnZo/V6nllTgn19oH72t/++52yG/k5gAIjIgbR9Asf2Z1hO1F/96mLkYPHhg9F5E2cXbFJs97HopgZLjpxC+ccU7f6j+Tj20uXhC6jZrZ4LMCouePg9vXJM8tPNTfz4Efzlqd5ciIspPXq4B5P1jscufW0v+x5vfH1kt9oVL4zdeE2sHt6kBRJoxAURkFcPVObx/ipDL4jUzBhQ+b7gMr558krMSt4M2nRo7HIuVNsvtDL92cdENSc8vD47X9LqmsLdP7IoLgrj48C7Ya8f2LdP+dkI3BAO5uz/vHXoHJcU93Q7DOR7q0Mk7kXiPADCp+J9uh+EbVYUJ/fHsmnwjcpeO1jVXOz0wK3l/0atjmqUyb9mpeaGDRYnpuMglvToBL++rPK6vUF9OR39QabeeXh2B987UE1lKmX4+W9OOCSAiixjeZfioCRhZjd9hLkn3bap+wz46x/gqcrrh1xaJZmxtDGd9u6m7wdmlVUnPU/d3Jzb0zVieU/vH1AuUxLV+FT7dkRjsp7yrK0JjXY7DRR5KBjmOtTMMc+uTy7T/m9H5L7ip6b/48cgPgL/9mDTv4sN2w4c39rAkhiuDYzJGaMQJAf/0TUWpEr7zTDWAKlZqLlE1WbN2uuYy8hUTQJRVvmRD9cjU0Wcenyb6Millxdbttd+I1+KhNH0AJXxHuX59FR8JzErroD4ioZMy9VGxTHYBAPwUOcGpcMhS3jmeubpP9/gOysvHO+9sQQlEAKOjR2J9pyOB9smDdwghcOaBu1izGi3fS0tiVdt3GPDwd03OEAnJeG4PxjEBRFl58gDmgEwHr3Qn/VI6+0l5Mdny5a3Hux2Cbm5+jvZ1Ak1uSN5nyDTTPCrLBZ4T25PI8mPQ39bfnRpAaZfhL5JMcnc/4vV9mNfjy0/a9nrxPmG09ZXHC35KZMd+MV+O1kwAUVaCnWxpUh9SRsiqLdjRkfXVSm8NLQoAx/h0KHizzhWTW5KClwbGA706YhuoD3Ftt/OCU3W/hqdV1ogngscX3YM/B1r7uzk2sDhlOYMraEqoTaNWiN4zmKwJIPNbR++Cd1ufJPQFMbjwEU2v1xvDFcc4M/qOlu9xp22L7A/ERkxgAbp+VL06YuuIZ+wLxUZN4ShqZ32fNC0cDqss7Q17C+1DiFMru3/VGc9DRj6RMiH7jjSICB4u+CLrcn6WUy1Nt6xUjvWrJgJ/vGlZsYkDRMwp/odl5eYbJoAoq/j+6Oqmx1yNw+uWbH867m26A5P2+HvrxJt/0fBKY3v8mXI/fBA+HwAwOXqgoTIMufV34LaxwD9GA7eNS57nw6OX3uGms7kzpLSp7yLKrS3YJQMnr3Y7BN9I3fpvD/2sumxyXSEdG2Ftma6YtLG/BlBQpF/HoYESTa9PTADNi3bD0Xttn/kFLjVbSazJFI9Z+nC/SOZs+0dvS8tzagu65dNpmP9d8oAIP85e59DajSkS3k1QuVVzS0uNdFdv+sT7aMmyb0y82G+PRjsjIqutjPUZN+tz4Jf0149GRvvMVluYtGECiLKKV72fFD3Y5Ui8I30fQALfR09BJFAAIFZDZ8/jbFl/Xaf9AQAr5G4AgOXRLrasJ60uRwC7HQ7sfhSwm7mh7MnbtjaG8cj3c90Ow1ccPam2KsmRtRz731W2E8HEqv9RCFx+VNeMyzt14aXtBNbfJ6we7wLGPnl4oTF2SdsReJo9PiIf6eNIk17NLQfiTcBsC8VXwhGJQdPWGEqMeE4gqPyV0tSw72QPJoAoq/iJ92n77+xyJN6ze6d2qvPsvABpXxjC1EfPxrmH7Jp9YcqIzRsU6U44cuIkxEEizdaktnV5/aNdV1mPqrpmAM4kU2oaM9/FT4zBS79Zj3+NlCPYCbQ/eWlfFefEtxnUmgDK0gn0ob1aa9Hnw1Y4cmEZHvhmDn5ZsNHtUMwTsRRDNKK6iBd3LUKltnKuYQKIsoqfeHxy87EuR+Itn99yHL6/68SW5/FdRjCg/Kw0V1M0cpex/Y7YuUMRCkPeO7nwG6t29W2Hg05fcu/QO3itoF9sGcolU4vvxB6B5DvoHxe+2PK4pLhn2tfpOgkadEPr49IpwOT+wBtmh+1NCWDmAODVg3Fa71EAgBuDI0yVvu/Hh2ec3xkVePf3FRmXSdeE7Kg9O7U8vuTw5FqQztUAUp9XC+UGQUOgvSOx2MXzw78PvAoY9qANBevcQ1eUJPVvZaXHQ5/ZUi7ZyxeDAFhke7EV/Qr64vnQe9oSQJWrdQ3XfVlwfPaFfK62SUmW1DTobNa4bibw9M5AzQbl+YS+yr5o4/ykxaSU6PvbUpRVN1gRbnpSAq8cBPxwh/J8zpfpl1s10dCvw+4bkw+GVOLNMUwAUVb5dABLVFyQ+edx0r47oXOH1o6Y4zuldqGApte3EEF9gV30GvDXj9pMfqPgZgBAtXTzYoMpjWyuCI3FpcGJbodBDmknmtJO19XvT6L1s1ofT+gLDPsvUL7UWFktwaTE8uNd6CK2oKpeid1sHxuhhi0Z558WnG2o3AG3tDax7XPl4Zj/v3OB674DbvnNUHlGpH6PB+zaoeXxl5Ez8HTztRjS4QrH4slLS4YDk99xOwpg/vfZlzFon4CbHR3n5zmgn2X6xuw8S7soOAnXhEYjBPVaHy0WDm59rOGi/umCj9NOnx3dW1NsVa6eG9ts8rtApAlYrty0wcjHlb/j+iQtNqe0Cn1GLsG9g2bZF0s0AtRk7zcsOq4P3vl9ectzKaWm5I7de6MjA8tsXoM3MAFkgS1yW7dDsFW+Drt42v676Fo+vt+KV+gRQuPPK1ioaz3ocROwbdvmeCUBZdSbJcH99JWX5+yqom2m3OHzvDGqCTvbMyfTNuCtqs/pg3Hq29f7W5FQ9rOJfbGFggFsUxQC9j0L6Jq+RtSaqPXNmFO/x+P3bh0FMoIgPohciKgosHy95IDE/Z+mfSH3l+n6EKL8E9SSAEr6vRhvgr5Gdta03HVN2kaczCnR5qSn4ahSM6uuScv3Y5DUVnZpRR16j2gdHbX7w0Px9M8LsxfvqXMn/2ICiLLK1xpARqXvIDqDYMiiFSvr1VzziGyl5Xejdk3xzfS1FkdjDPsAMifTNiBVHutjzfczdkn6kcUCmjvyNEfLiDXJlOUzXZOnmxUU1p/0Jtb4IcpF8f3YRW+Mw7NDFmRcdti8DU6ERB6nuQ+guLR9EFoUTIyfrmUsSyVH0tfebbKzY3eNHT5Ho22X+3DCSqujIRW8UqSsAnnSIVYq0wcLrUcvvTWAVESgNCVrFMVZlrSRD2uMFKI5+0IaSCh3vfYPWJG88cZvzhtR+NdBgdWal/204HmcG5jaOiEaBT6+CFjyi/qLVPYxoqlW83oB4I4BSj8Mz4feQ+Tp1rupy4r/Bgx9QFdZRrxSmLn5zqmB5CZiWmoMOXWy/+a1R2Vdxn97xbZuDg5zO4TstqZPZBpSswF463jryrPDjM+Ab/5uXXnhRvxQ+DiOFkuSJp81+WZASsxbW433xmW4QPv5Ppy86QsAwJmBGdbFRb5zffDX7AuNeFh9Xn0FxDsnYh+hnE9tj2rVRRth0U1UD9F9Kh0/F/jhDmD0c63TFw9Ju9j8ddWYt7ZK3zpmfQF8dV3b6dM+BL69BaivBN45GZgzSFNx3Sr+SHreEVuVfhIn9s34un3qZuK7wicQgrmm6fmOCSALeLGXfyv5KWvulHQ7Z8OfUkE74NznDb00/gOWECje51S82nw5PtjhXqORZDQruo8t5brtgECpZWXtkHCSYma/4JWKN16JIyelfLinBufi3cJXWyc01wEl44Cvb8xUiCWhxPfx14RGIxhpTJ455V1L1mFGv4I30k7PeJKcZuPd0PHIlse/H2vN+9quOHvzrsSbKNc1Zbjo8bAnCvR3Qvx0c5qLBTtpvPDQZNbnQH1FwoTs+/PaJocvSH66G5j3jXXlbVqEIwLL23S4vlPVXCCi4UbJtA9w4fo3AQDvFryaZWGyU/z84/KjuuLd649Ov4yNx/f7CvRulynBLB0JUbYA/wop/WqdH5ya5jWKD8Pn483wJTrXZ5/xkUPcDeD3F9NOnre2Cp9NWtXyfHZppb5yf7g9ud+muJ/vBeZ+rfQ/tGEuMPhf+sqNOTf+HadbR4Kr1r6IowLL0EWUG1oPKZgAoqzyOQF0zbF7aF42tQ8gXSn8E+7UvmyCI/fcHoAyAs75h++O1yOXoybYyVBZ2fwUOTH7QnlPJDxyu2GPBWTLf2SxpCZg6c7EY32ISY3t6a2LxntSf0uyZXrGDFCaKcry9zTdidMuuNqi6LKLx79O7oDx0UMdW6/bPohc4PAa3d2OM9aOsdEnE0vw0+x1iEa98zvO5/PGRG59Dl06KTXBj+u+A849ZNfkmV68Z93mGKg9yEYUoHc4+/7cyHcxMpI+eZZJ1TH36H6NaRmuN6rqm/HH8nJc9MZ4/DirtXNm3d1VmIhBC+39zSpNx7iHMYcJIAvk+oEu19+fVo9fdDD6XKkMZ3xY17ZDvRoe1ceEgqCyw+1QbH8VWG4H2emt9WP5ATiDUYs2YnV5ner8dG3C3dim81KaBFBTWEn8RFXa8OeTdH0RCWTrA6jtZ7pdO6W2zp1nOFub0YctY/3J5SqLtnasmsGTP83Hv76YiS+mam9ymlbGz4/HAl9Kt+/x5FepNhCBJ4PN6MJDd3M7hCTnvTYWa7a0Pfez/rjkTAIonue2s/XNpprG7Av5HBNAlFU+n7smng/9/eTu+MtRXfHjXSfh1auOUH1Ny8hJKqOAnbzvTnjo/AMtjDK2OstLTKZpZ+vDK52dRdt20Eel9IGgxXbjn006fF0R/D1p/rF14/DP4HetE2o24OqVj6I9GlomCUTxUuhdHFE3AX0L3kAR0g8hbsTNH0/Dma+MUZ3/32/mtJkWlf48AfOyh0Of46TAXHw8sQTjlioj5qRLtBW+1BUAEJRhVL9zHv737ZS2NYVWjrMmKClxaWC8NWUZ9CexQnVe6olhfF+UcW+TZv+7b2elw+b9O1vbcfNHNx2DXhcf3PL81lP3xin77dQaSuxvRAYtXS+lqC0DvroeaKxJP7+5HujVEfi9t/6yN85TndW0YSGib52ARwq+0F+uUd/f3vKwpLgnSop7YuHaCkwt2aK7qHtDX+PswPTMC6Ub4n7mAGBSrP+u8tbhnJ8OfYiQcKYDea9zq4sI33dNETuXvCT4BwSirg1rHzFymWziPFjX2VakGXj3NGWfNlt93/NH41/Q9Osz6FfwOjqgDrcHf8IlgYk4Zm4vYG2W3/3EN4DZX2mLZ8Sj2mNPQ+ugE+k6j7ZaPtz8ZALIAr7f0Wbh1EgwnqPytR6+Rye0L2xb4yZ+bdYcbA+c8h/g5uFpXz/gluNw+2lp7kAXbGM0Utt9Hj4LAyNnuh2GY74r6qX7NR2mvZG0L/hHaGjS/H9veQb3J7aLH/0sDqkag0uCE1smdUE5rgz9jn+VPYlLgn/g5MBc3XFkEtbRRCAcieKop0daun4CbgsNweeFz2PFplpc/8EUZWJCYufQJ0egMZxck2C7DX+gevq3WLg+5cK2WV9nz2oEJF4rfMuSsoz6pDB9vwVAhgRQhhPt1budDwC4relePNL8d5Sc+3HCr9PEyd1hVwN/fjNp0hkHdMaNJ3Vvef7IBQfhs78f1/K8ItQZ74Qvwo3NSofaNzX91/j6feDp5mtxddNjzq944hvAwp+UzkrTWRI7Jo9+Rn/Zo59VnbWq/zUIlGUeHctyaS74Jk6diive+UN3U7B/h77H+4WvZF7o+9vaTvvxLmD4g8rjn/7ZMvn6kIYOgPPEFy6dNxWGlMu7UCDNPtIHlyyV9a19Tu2IGuuvsy7p1/JwY2AX4IS7cVXj420WC537lKnVVB2rr09OXT1IrJsJrJ+lqdzrGr/ERcHJ6Bn8DQ8VfIm+hf2w75pvgc8uy/zCXx4Dvr9V0zpQnb0/zXfCF6nO03+z0b4N2cna+W5hAoiyyv2fgTUuPEyp9nnyfjsDZz0O7OJyR3AWejT8d+y5y44YfPfJbofiiKjuYakVZu8ZhJFcQ0BCoFq2N1mqMYOmKQdz/v6dVdMYxsPftk38NSOE4fPW27JOL9TyylT9W6jchMi0bUaDhejWMBCBgy/GoX++B91OuMyaGooHXgAcqbNzYyHwQrgnlsvdAQCjo0dmeYG/fRC5EJOiB2df0AJp+89S6zcrak8TrUjYuWaatY1hVDek75A5frPuy6lrHIuHMmuENaO86tXzuD1x1xn74JLDu7iyft1Sfsdf2L0NH3U98K+ZAIBdOrYDzn0Wk+VBbRY7++i20/TYetjNpl6fUUB/jdJ2IrVpk7NneHOje6vOC+qsbGBni18fNmbQjQkgykrt5DsfXNFDeyfQx3TbASUvXIgDdrW2eYFXXNljDxyapu+jXGT0uKLnLlW6g1dqAshNAxJGiyB7pV7EfjdzbZtlmhFE31HLbFq/LcXqkqmmadsaQAotJ2kdikO45tg9TUSWwsCHlVpT6Y1rcjsB5ITyrY04rNcIdH94aNuZaokeac+5TAjO9f1zyJMjcFivX9LOi/9OKuqMNh32wI6ALNG+MIj/nnsgQsG2l3kH77YdAGC/zts6HVYGydueA6182uhQlK4vTWczAbp+gYHsI1CmKoaG0fxslOn9ae0DyIkbVoE8yAAxAURZBSDRpWOx22E4T0ocvdf2bkehTR7srJxktLqxkQPTMYHFuDGoNE24KZSu2aC5g138nXTEVjwZ+gQIJ98Bao8G/C/0Edol9EUEAD3C03FVcLQnaofkom2R0CljQlIh3p9HqrcLX8eKomttieWtgtdsKVePjqIu+TNJkK4/ESEyNwGLz7I+uWUgAZTy/GK/3JX3sAnLy1HdoFLz5pdHlX4xenUE/ngL2LxUeZzQbw5+eRwYdANQEUt0j3kB2JilGdeG9P0ABR1KAP09OBRPhz5Mu38AgF+KHsT3hU+gYM2E7IWVjAcmv2tNYM/sAqzSsE5ykPq+8ZLDu+CXe0/F2Qfv4mA8WUgJ/PY0sOQX4Nf/IXVEVSe62hh+76m2r0O3GZ+ipLgnrg3+isPEctwWjA2Rvmaqod/v7aHMQ6wDAEY9q+wvFw9rnfbqn3SvK51oStrhidCn2BFKP5zZKht0RkVsOeUYfHZwhiUxpZMPV1RMAFFWiReAjzXfpLrcR+FznQiHEh16BbDPWcCprX1KWH3Bsya6MwC0HUo0hxlPAOlZh+Ly4Dj0KvgUAHB36EdL4ki3ngdCX+Gm0AhgzqCk+beGfsYNoZG4OZicfHqq5km8WPCe6fVTesnftbYfbUDYk4w7Jajewa2T7gj9pGm5h5tvybo/ytiGP76TPOQvWkMjj1mxaau2BUc8DPTroTxObBo2sS+w4Adg0N+AplpgzPPAR+dlLuudk9pMWryhBjsKlU6nLfZ4wYCs/escGViGW1f8K3thH18IDHsgZaLB4024IfsyZL/9/k/TYkII7L+Lx2qqV5UC414GBl4BjO+DHSMbNb1sanR/rJDaRt0SAJ5t7oknm29IO3/3Tu3wYfg83NZ0Lz4Kn4s+O/3P/Zursb61ni34ED8VPY6H4x3Nf3A2MGuAPesc+5Ly94urW6dVWdMkL/UM5ubQcPyv4BMA2ZuAvVTQH0DrXir+Oju4/bU7gQkgyiqxWt6AyDmqy/0vnH6n6l8+2AMUdwSu/w7YrottO6wGFKLkhQuxxw7u9EXjJ1bXlrGytHgTm5qGxrTT1ZrgsAaQPUJIqL2gs9PWXBXUsK3t3TAAldvsjU7tjfStkbKTPCRLB5jpGGoClmFmO5/UMrXbgeqdg6bz2q9LrVlvNNz6nUb0N48497WxjtUAsh/3Q77WsavbERiX0jwzqvH8+4qmXojoaDr/XuQifBJRv1n9VPhvGBE9Bv8L34AZxSeYvqOak4kEnZ/JtU0PJzxr+4HE95/Zjv9O7mfZCXQaQoiOQohhQoiRQojvhRCFQogPhBAThRAuDPtAdgtAZqxqn+tuO3VvdGynv62tfuYONHb149GuwDv90jjF6EepqwaQQx2vxGOK1yZatK7SkfVSZvHE+tbGMBojznUi63dRCAvyZWYKsPh364UOmHzGyn1nYzjSUjNIb6kNzfELl/ztJ5G8ym/n7Kn9vAVV5zlFGQrcyLrNf/ajFm3Ci8MXmS7HFjr3v4nNvjK9Umt/s47clPTbz8cAIzWArgXQR0p5DoANAK4GEJRSngigixBiPysDJC+Qmk64/ndJ7ox6lejhCw7C7Ce1Va3NRbtv387tEBxXKIzdadBzYEpd8pJA2z4UHgx9hZDJi4v4bzd+R+2g5R+kWbvi6UfvQsNnVyO84OeWaX8PDku7LJkT31ZOfPJbdH59L5ej8YaLgxNxuEju6Lqr2JSylEBERwYoaUkrbmRYnrBhAkivq/pPAgAcIZahX0FfU2UVlS8EXlA6CRfNdUCvjpAv7aP+Pf/2NDDjU0BKhD67GAMLnkGxcLdj1bR6dQTWzwGe3wOo0dacBg3V2pab2A8Ycr/x2MgmPr5qnf9D0tNuTUuSnrvRHN2SXb3OQvYUZQCAwbPXoX7cm+kXKp1mNqpWDZWt/aX16gj0Oyb7a8a/0vq+qtdlXTwqW1MNqX0AAcD5wakoKe6JBwoGtZmX6ofCx7CrqMgeo0kBH/+UtNKdAJJSviWlHBl7ujOA6wDEv7VRANKOEy2EuFUIMU0IMW3TptQTOn9zonMyN2ntmf2GE7vZG0jOi21HB1xo7NWJm+HBlwLnPm86IsDXpxQu0HGwb0zuN6JvYduD/UGB1WjfZthOfbYrmxqLTPkmt61fhwNF2/bcAkofE8XLhyE0qLWz4ZY252SpeALok8KXXI7EO3YX5fix6ImkaZ8UvNBmuZP23TFrWR2KlRFddtgmoanYSfcA23cD9os1AejugU4/L+vvdgS2+ip8OgDg5eYrAABhab7ngSkrtwAAfih6AhcFJ5kuL5Wo2wy5cX76meNeVvrlWDcTodUTcGIwS8fRbnr3FKCxGuh7hLblf3k06yK7oVxZbur75mIjSw0Mn2lpeW+HL7a0vKyWjUx6elLdby2PCyxq+rNIpozqu11XYJdDgYteS7u8lLAgC6Tv9Yl9A8b7hmzj/bPMBJTZ5iXZlxn1DLB+tvL4q+uyLj5HdgcADAyfYep2x66iAkcEVpgoQbt8aPVi+EgshDgBwPYA1gCIj1lbDSBtt/JSyv5Syh5Syh4777yz0dX6zuDI8W6HYBr7AHFK7HM+91nzRV35CXDCnW0mD40ca75sUqU1WQrAtiGJUzU1hxGNyqQ29YlNFnI9ge1V8W1lO9S6HIm3bSvqk56P+c/p6HPlEVlfd96fdsWzl/0J952zf+vEzgcC/54NbBNLILXrBFzxsWWxGnJAlo6Hfe7B8K3o1jAQ/SKXoVvDQDxc7I+eAkbMydLpacToUOvW6dYwMOmfqub0o+ulWrEu+81Zng9607Bo6rmdueP6Z2H1/j6dpjb4wcfh5Jr5v0WOVC2jW8NANKAoeWKoELhjPLDPGWlfIy3Y1nM2kRDvUL+hKuui9ShGt4aBeCT8D1OrVOun0g4iD5pmG0oACSF2APAGgJsBbAUQbyOyrdEy/SzXD4i6LmrJPK8dMLwWj4eFdNypWrLBmZFjXhyxBHs/MlRzO2xyhpMnM34WTungs9tO26BYQ79kQghce9xempbVJQ9ODO1ybPcdcPeZ+7odhibZ+vWJutxvV0TqOy6vLq9Dt4eG4JHv52Ll5tak89rK+gyvSrPe/DvF94W21yEmOy/20FmCWt8wqTevLB+Ew3BnkLl/zlzXFDvX1fkh+eWGo9b+iPwspPcFQohCKE2+HpZSrhJCTIfS7GsSgMMBLLY2RH/zx6aeWb4mgIRNQy5nZfCoc/genbDTtkW452x2w+WW3UR52unjl25u0za2YcsaR9LlJwXnozbSLunAu52ow/cFT+DWpvtwfGAhAOC+gm/sD4ZaXBf6DevkTtgnsN7tUDxrW9Rhd5XfVCJnOumPMzAKWE6cCZg36LYTgGWZhzHXol/B69gkO5kPKINzgtMzzg98YqyptlUaoW8UvF37dsUPhXvh4FmrUDi79UbFNy/fgX/HrgT2DmzIWMbwwgdxYMCa4aDzzUn77giU2rySxMRDDiUh1JKxdicTrLgCMBLhZYFxGB/9kwVrt0/V3OFo3/1Y1DQ2o4OO12kd3c1tAZkrIzuqM3L58XcARwN4VAgxBsr2fb0Qog+AKwEMsS48f5AQeCt8Sdp5y2QXS9q8u+mP6EG5W40xA8dv9F7QGyjaDiho2+lygyzAN5FTsXbnU1Rfvl1xAaY9djZ6dNtBdRlDb+lMf1TZ94IBhen7Xbrug8ltph0VWJZmSev9O/QdhhQ9knSy9GXhMzgysAxTi+/EcQGPjjSRBx4o+MrtEExLrYZvpf8VfJJ1mQ9v7IGh/1bfL2a110n6lu9mYl15Zt/O27adqHYQ0nGOcVFwMm4KjTAWVI54rPmmlscXHrZb1uULRQRHBFa0GeDg36HvNa+TyR/j3rr2aFvLnxPdGzjqby3P6zvlzo1AtQTQoMjpSc/7Ry4yva63rz0Kp+0f66ZEQjknL9ST4gDQ+eCEJ/rPul8tfBufFr6o+3VO2m3GK/ht4UZsrsncR2Wp3Cnp+ayoP2qAIpr7I7Ma6QT6bSnl9lLK02P/PgFwOpQaQGdIKbM3CMxBL4evTDu9RrbDvo0DHI7GWpuwvdsh5IcjrwMeXgOItk0WPoycj9EH/Q9d7hzsfFwHOdMZ4K1N96Jc6jzQeownR4OJ8cudF/KXXuEbbSu7E7ZmXebMA3fB7p1MjFS4bWfgxH9qW7ZXFbBd9ottUhzWtaPbIXjWU83XG35tt4aB+C7a2oH5mz2PwtN/PiRzP0Dkim0KlfM5O0cV+iFyIv525pHAbofjss5D0a1hIKKF25kq00tNddRaISySeyY9nxQ9OO1yepx/6G648/R9AMT6AAqGgEd0Vt1q18l0HJ0dGOnKrL9/knk0sm4NA3FyY/IojZXogFea/2pnWBl1axiI8xuzD5AjLOp43MssqZoipayQUg6SUmauP5qHvLMLJT+TALZvX5DzNbG8dNKRa/jZkt+kGzLWHvb8Nm49dW9byvU17oYskdrs8brj98LlR3V1KRrKxu5zt/v+7wAAwGtXHYGrj9kDh5tMvnqpD6Bs/XFppbWpcPy7crO7N7+cr2WL8soeXfHtHSfgL0ft3jLNueN6elo+WxFlH0CkkXd2lZSLJIQl/Uh4/aDipZMOK5wamI2x0cPdDgMAcHVwtNshEGkSQBSXBCZm7YfFMjZdnO2yXbEt5RI9euFB2GP79ti5gzKykRACr1x5ONDL3bgoWbvCEGqbnKtNsNeO2+CFyw9zbH1OuDI4xpJyPr7pGFz21sSsy8UPB26eje4kql1cuza7YAu6BTb+f3v3HSdFeT9w/PPs9d7v4I6DoyNIb9KkqHQboAIWUBRBsWPHxCQWjOZnjSRRI5poYo+9xkY0EsVo1KgoliBGRQwo6hXu5vfH7N7Ozs7uzu7O7O7tfd+vFy92Z6c8t/vMzDNP+T4hP//ostl4vF3f7n7V34sq1u81kfESPZoMARNhfK6FjrWSbjIzUrviIN092TrakS7ETnSRjajnvpHX6SRSaRx3sbI3FbBIPRe3HBN5pTRydMbTXJN9Y7KTETetk84Y1lCRD8D43pUcvU+PwA9rBofYKn3KGHfs2S/gvdNxsqYPrOHwUfWM610RFGfpvlaJURWKOR6J015uDS5f3X3iPpw3awCFOcHt7TdxiKvpiYfTjYVXtRwW87bHZT4RtOzh1n0s1325dWDQ73zrnhlRHc/3l8d0/R6z3LSv9L0HbMxdZblcG3w45Fe2V/6Adzid17NtI1xPWzh2rgNKgkCLcA5sujTZSUiI/QZUs/7YMe3vGxrvdG2sebQXanelRoG0ofFO3tJ6xdaF+OLAkFz/0apdDdoKwJIkxClKM4+1jmFC47VJTcOnbdVJPb6ARc0X0tB4J+tbZ/LLliOSnZyEqVI7k50EEYfHTpvEpjX7s2CkxZCkohr9vnTxLiipN3wQ/YPShS3HwbmfWH72T0OwUV+ZxVx2adH88fZWNJ8e9fGNNrYNaH99W2vgPfau1qlx7dvsukXDQ3427NQ/c27LCY4eLxpulg/D+crGrHDrXS5fLm65kIbGO3ipdVD7sl5VhayY3Nty/Rs9Rzpy3NQoqQY7q3lFe364ofVQx/Z7WNNPOKXlVMvPFres0ePOeK8xC2oe52d7lgD2e2TmeeM2VRbmBH+4MnQPok0L/q5P5hIgfSuAQlHzb4JztgQsO33/fu2v39O6835b8oar7iaf7Vr4IZKqsEuCUpM8UgEkIjpzej96VhYkOxnCAbMHd2WujRlDkiXVh6gligeNH7AofCSQ/BbJZ/wN5PdwU+K+25mD0r9gmZ+dSYXVw1OQ+L73VjyQYT0dekOlxQxkJlqI1/Gy0+ofz/Fys4InivDpXVXIgC7xBQDuiH7UrPNBYimiydMZDkWG9g0DTDUaeoByp8UyocWNR46g1uZkAYNqS/jl/CFcuSC64fuaFpwuJ0I3pIPa0jxuP87fkSBUYO/ECX98T0b6V4+k/1+YIBvP399yeTp0/7O6gOVnhy6ACHc4EaZi4eh6KgtSoaDUeSzIeIHHss+PahsPbfyAxA/p7HwFygtmD0iDO4l9B3gSFPvHx+UArb7ddy3J5TdHuzsddGeiocBjHdi1KC/4PpdnqjjRAorA6fOgduzEzhd8/EcbDSaJuobaPY5TgaH36eXu0LZYteFhjgsNjtE0hvh+i2gryQ4fXU9Jvr2g0eZjGeVmyrOSFY9Dgb1F7KQCKA6XHqJ38/QoqI7QtXBTW99EJClhnl89JdlJCDQ89ilVQ0vSI1eIQkEyWhL+3dYj8koOSdceDldl/ZaBnk+j2uaR1nE0EV3hw2lOtU52Bo2aO7/Vx5reW+TIsT34eyLid8Wgptj51uf+niin3Y1XH+sGHKeFPaMGOTdEIpVo9h+H21/duWearS3aUJDhPffGBcajaN57IW+29WKP5i/mjutdwbULh/FW3mj/9u3pjI8x9s4XpviQ/7WIF+nq/a7baPf2HcZOrYCczOQ8Vvyh9YD219u1UD2g3PvOjXn2AZtxmLqWONPIk/zeFNZ8lS5XHzGUW4815cn82Cut/qPV2F73lGn6UNB+NUUxHy9AUegKrdzs4DhPxWWpWTnnFi1EhbzZna32rvFu+YPboTA6AKkAisOohshBoH09gFYXX+V2cuL2bls9DY130NB4J5e3LGpfblUfEanCK6Eu3gUH3+D4bvfqmtxu1Du0ooCx9MmYAX528+UJO1aq9pZ7ujW4xf7fbT0Y0vg71475UNt4kt0irSm5PZzdsjziOmc1r2BA0200NN7h3IF/uhN+upPmfD0OU0FOJg9eflrAKtfumefc8UI4pOnnEdfZeEFiKk9c1TAxKF5aQl28Cw5bz9bCjjV7z4bWvW3He5nav8r2fi/Yc7z9ODJK6efL9Evazxsu3kXj4KM4uPkX9Gn6Y/uqeVkZHDysjsHnPkND4x2mCqDYr7eHNP2cu1uneuOd3MEu/MPPzm5Zzk70e3m/xttiPkZUqvrr34PLrm6ZT0PjHdy1ZwoAa/csYkCXIj5ZO8fWtdMp9+zZlzta/dehRc1rLNdzutJtUtPVtKz5hobGO7hgz7L25fe12ZsI4+YloxxNTzINaLy1/bUvQHNduR464tDh3Zja3xRTsN/MmI7T0HgHX2N/ivsp/av5ZO0c21PAh+SLW5Yf+rlvcLey4IXZ+fEdNwab2+qClg1s/H3gglm/bH/5dlsDAHObLmGE556A1Roa7+D6PYfYOu7MprWoi7bbWveW1jn0b1xva103XNc6jzObVyTt+KlApoGPRxRP5B1hNpAWMon00HnCpJ7sbkr/6fGA+G8YDnOuQ0bq58VUYjXefA8eviW942Kla4+saET3HTj4fXnvLU+dvi/bdv5ouUoizmK5UsQn2tt+15Jc2O1OWtwQTaX91AEWQeXjPGXaz0+LslhxXhZ9q4v44Cv9Cz11Wh+WTugZcPA2QxtoPNe7wO8hcD97tCQNAUlYi5Gi1fs3K7SwAard4lH2hpM43cjUpnnIzPAQa0auLnKqITX5V+q/njcLrtFf+76NxWPc6EEu5ZJIrL6hlqDHff9aGd7hWG14qCzKgV2B69k9b9YcNDjsdWdUQ2AFWVuS+6B09pwkTbxOSUb3jCS4cM5ALp/nXivlwK4OddNMQ06NF4/GZYeGmrK387CqAMqkjXS/fZTkS6yoNougjmZuFr2ri3MZ3t2iVRFYOi5xwzNFYmRqHatxRWG/6BNxtRjub+HOz8wMD0+fOZn7Vo5n2cSenDm9P+WG+HcbzplKQa6/kSee81ihce7MAZafBT94+Y6XPvcPXyyln8wdQI8KvWEkkcOSMm3GE5nU134vNDta8SSlXJaK6gwBlpX398jOCtPHIM6v7bFT7Q2z64yqCoMbr1vDPO77Knha8QTM1gVw7swBTOxdYeu4E/uGH5qXn53J+bP818lYgnk7SankV5wmk1QAxcNG894b3qlIO8JNokd5Pm9dnNxxkR2tC7wrsvQuow+2TghY7EgOKu8FPSfbXn3x2O5OHNWWVC0Qv9cW/B083upujIVab2yAnVryehmpEv80nf9q6xlmzfT1rha5kuU9LXHniFFp/4mu7v/p1pFstzG1cqdRnYAYTJ+/7v4xHPRM24ioezkFMlzzY4jDZOeeMbJHGRfNDf7t6svz8Tg0zPVzrYIJfSp44vTgh9L3tHqLLeCtNLim9h2l/2a+B7m8DP/vkcgh3eb4aKFyhdOTl4R7qE6s1Co7vZHjne2peq8wa8WX5oG1nW+mO7u+7DXf/6Zaj1V778rA5wlqvT31+s6gcszhAGzXSulbHTh74sopvRnazeaQu/zIFUWZhtm1klEB1KPCPyTv3QTGOE1FqXL16tAsCyEXfsGQxpv4hxbuAhhsSONNDqUqeiX52RR5W8QCOjS7eI5OarqaoY2/Y3zjdfRpvJ2PikOPiY4USLupZxrEogB9zPB5W7lkz1GBy2P9Hc7/DC7aAed+qlcADTzIer2x7o2HHdx4s631rIqMG9usW1YTxfyAv0/j9TxWdmRgZel5Wx07nnb+tvbXY5t+zaLmC6PfyXFPwZCFUW82rPG37a8zSrsxpPEmhjT+jidcrvBKVe9qPdqvT6H8W2tIXIIu+tr/2vzAXDcSzv0kvv3X7A1nvsd/lr/HipbT+ZxKJjZdy4ymtfHt1wkTz4AL/pukY58Jy1+IejNzAOSO0BBkx6nNJzO28QZubZ3J4LrwDwe2K4himMgh7geIeCuA9v8ZQxpv4gv0Bx/j9Ot7Nf6ekY3r+FDrZrnp61o/y+URrfnK/rouni9Nh9/F3EMXs9+Aan8Z2PBjJ7IH0GOtYyKvBPH/3ia+ISzzhvtjrtTZnGo8Xoc2/czwLrV6MjzqmaqXN8NVAMVwLTSXIx9eNZHKwuT2VN592gdJPb7Pt1o+Xyx/m7WDHqTvoWvglNfhpFfgxBfh/M8Y0aMczvuPXkY491OoHw3nb4OFd1A5ew2DG2/mG0yVahd+Afh7dIV04gY4452w8ZF8jjQ0Khufnfs13sagxluCYxU5bP2x/mvFO1oDQxpv4ozmlQC85Y2F1FlIBZADLFs6svJiihGSCnFFZg7qEvDezdmntmo19OlRz+dUsodMysMMO/lOCx9MLSc38cHWXJNbHDQ+NubfIacIMjIhrzT8eh73QoL95axZEdcJ1WL4gUVAu2R6Ze0x/HX1tPbKUgBynWuNUjn+FpgmstkVSy+g4q5Q1hD1ZjvxD8EszMlg3vhBfEshqdbCmEi7KORzUmQmj4wwccnKe0Ge9XAx2/LK9LyTU0Iremv5Z1oVzUmekQ6A7MKkBNQE9GtnZuwPGmlS79Pua0r4knJA8cdlY+1tFOlLiOFLirvXaLw/TGYOPepq9bSYbl8/ksuOKILVRnNM21w8X3Iq9J5NrZpmqIjzfwmJ7AGkBZWVrI/tdJp8PYD+74hh7cuyMhJzsv9gY9r7ZNGUilzejMF3BObnwd1KgmJ1XrtwGOvNM465qLDMIrZZErSh6FJbz3mHTcGT4YGK3noFXEam/gwAkFui3+N9v01OoV6m8Hjav9uAS2KWtzJTi1AB1HUIlFhXdJvlZmXw+6W+hn7/wZrJ4nvy+AF3JxhqM12ov6WAT72zyqVEOSeBpAIoHhEKDzcd4+/N8qvDh9raZUNF8isxrl00zNYMZ0544ycHBHxP84aFnmIxokgXqQ5mUt/Ah86OPCt376rCyCsJZzlwPvRIgetRqutRkc+vDrN3fXeXAxcIb+HIfGtLiRn6wlV+uS6+77bM27Bx7IQGB9KSfMbAxiX54X8X37W/rtSiYB+iDHXzMaM4fmLkIVJODhuOdU/R1CHdujSNelIqPQ8cMare0APIf89JbAVQclj1QPMoRX25+72AUnXIPAQ/ZFtzJv2+hrhrFw7jTyfsw8HD6phinnHMJJGhDRLF1fPN4UmMpg2o4ZO1c4I6GyRCqk3uk0xSARSH0ly9x0RhjnXPiQMG1rRn8AFd7AU3bmnVkjfkpdcUAHIyM2iu9I+pdrP1sjQ/uz0w49D6UjLiCcrVfZxDqfIKO37ZfdctDJxNw63f4R9t/fUXtcPDr5gAz7aOCFr2htYnCSnxmz3Y5k0q14XW3rjEeC75eoJ18z+slOSnbmujm44YZR2/w2dj2wBeOHsq80faa/1yjFUcr+42e2KEZV0BtFNLgQrcLgkISN8jRFylGC++vnJzfnYGn6ydw/GTesW0n69SLBbT59gLCgqwdHwD96wYx7QBFgFC+xwQ+L5Y7+25/8Aa1ljE7TGbPzL8+RlRP3/PVF8rcFSiLCP07ZJq94g4FOgNVLMGd+XYI/QYIlT5y66JrQCyd35qytkYQCdOtg5LsOGcafqLmr0dPZ5RwN9cv49rx4mGlqP3hL75GBsVnfX6UJzX2uwPhTxqn+CKm98ePZI1c/bi4GF1jLMRrPiTtXPcm9wkM0Tvlb4z3DmewTNtIx3ZT0leNpQlJj5ZqBkD259JXFBZmMNDqyZEXrETkAqgOPiCWWVnhr6pXLNwGM+cOZn87NDDa6Y3XdH+2uOBY5rPa3/fesobQev/Z+6d/jezr4oixWGc/hZMu6j97bbyccxrupj+jeupKIih6/uMy6Na/cNLZ/HAyvFBNc3fZfgLTKFm02g37uSojhnOd6qgvUIsWcpM37sbQ/EmNl3LEc0XwWlvwuAF/g+WP6+PF04gDcVvilYFLb+3dd+EpgPQx0171ZXa7AVz+tv6v4NvtP581pWWixc3X+B/s1ofT26MFWL81Z9ujeImH2sPoPM/g2VPw4gl7cfuaerBNabx17Ht245Vr1kvN8a/ccHS5nOCll2xIHxQeuO1Olzr/jktJwQvPODnUOGt3BxyBG2rbAYAPut9WHy3/nr1B/pY/5NfhVHLvJ9vhpM2wqpN/m16T7Pc1WdaZWD8DG+eMceqMccGeCqafBivuVfDyr+H/BscddS9IT6I7do72Bs803aP2r2C47NpZ23m/n0fo7E2+CFv/6ZfxpSuWD065VGmN13BZ5qphd1YDjHdNzwexehQf/9MU2ypk/8BZ28JnYCxKwPeRmrpj+jAa+D0t2k8+U0+MMbqOfujgNWObz7LentDGcFXchnYtZgxPcsty00lhf6eIfetjKHB6tQ3ot/m7I+gwPs9HbY++PPaEYxqXMfS5rPt73Pyue0VQIBedjj1Deg9tX2RsQJoUfOFbGmLo3e3TVvbQs/y9XFbDW0OD3M/eb/gB9Vh9aX6i9UfwLKnAj889xM452Nb+45UqdX+7WbmwhiL+0sCDW/8DQDqjHfg7I/ar3shnfYmDDsSztrMv6beZvs4Z+zfj+HdSwOW1RTnxlyxHrNSb/DglS/r/5+9RX+dE6Kh5PDb4cx3XUvOFS0LOc+qjBGFp8/Yl5uOGUVVUQ6s+Bus/tD/oUujK7IzPUxsuoaJTdcELD+m+TxGN4YoR5vZqWQ963048732e9OQbqWcMi25DcupQCqAXJablUGf6vCtp49esrz99fpjx9CEv+CQUdEzKDZLa57hxhtvzAef0u7gCazIel3rRxPZVBTG0PpfFl109cwMDx6PAlOwsYIS/w19j4pw83awi0xmeYNj+4rHAQP9rZJuDAH7TKvSx8+b48XUDk94j5bV0/uzan+rFtUkdHUu8hdWbWer3GIorYcCi0JoWU/oPzN4ec3e3HnZuf73heEfaBoNY5S/ixQvLNZuu1l5eutcmD/8Kxy67lipDG5V/UJVuz4E6Pm2YVFv063K/z1MHRD6t9tqfmAGvVVwsLflvLQHyu41p6gLZHlbGgur9bH+Vf38v1dRDVQPgEpDASfHOkbVlpyBfK4ZWk29Bb1I15rPNGenUw6rrAFqEjADF/hjHpjFeG8Z37uS19bszwy7Xd0t4ruoohpW7DeI3F7BFQYJ/R2AOVMmstlqVitj/Ido7hsZpnt6TmFgxYJZoenvjTeob0YWlNaTW9XAmjmGe09BYE+CcK3r7dFvvNfbx06bxN0njguoRN20Zn8+WTuHHENj4cgeMQyzL4+hZb6gQi/fQXsPqwBFXfiakujyUoVFzxdT2roW+8uxr7f1tb4GOixcXJyvKHM+CLtFj6LL5nl7lxRWQ7bpHp1XZitQLoCqCP+A2l5BVNo96UHG8ku95dTc4qBzx1JZg57mohqOm2r/2q6U4oGTJvDJ2jmxJdRpvvtFQSXUDAqzXi4U17qWjK8pjtxAHkHfmiL/80ZOYeC11sXwGp9p1XymVbNoTHc2nDOVN38ynUZy2E6pvR1U2RgxU9RFj21ouDedNb0/Y3vq52JKDHFPAqkASgFZhmnxelcVtk8B3Rnt2bMn4L3xQaSiJHHDEPKyUuPUME6/WJPm+aJ/TQoMM/FxeLYQPBmwp8niONYFt2sWDmNin0rG964g1FCughBDT9s5cNOeuXdXyvKz9BkkkqgiyTN9hHL/Sfa6EveusqqsM88QlfhrzpBupWQYK919MYC8DxfVRTmW8Y0SWmBKidhusT9gVUbTgBJlHtiDs0NaUp65UtvBB1+nexH4inV/O3dqbI1orgj9fUU1a5eN732YqRdISwLzaugg0E4fyH++br5kFh9cOovcrPQ4J6+KIq7dS+cloHcmKTQVRYpF9f/pnP7u/gYOxwCycvm8wdSX51OSn8Ujp0zkVtuBvGNPW3Zm4P02leNquSE1nnI7Kt94T4djz+zV1dRa2zNwCEzXLt7WxLxyKDG0xtXHGAOiJLhF76h9ejB/RDfe/Ml0iw1MyntHdbhmLfQNsiVD/043Ku/QC8PftDU3xmlT00Cf6kIWjXYwcJ3bD5vGeB1JHkoXE8P305RnaL23OsfM+b/IorVfeax7Fxh/B8N3NrqhnD8eP5aMMF0xPA0h4pUAZBXgRGjMLiW5/PMn06nsEaZ1y00ZesVPlic1b1V2AwpecrBFN2VzrxxfobJhUpypMqnZG7qGLszXK8O00nV6Twff152fnWEZ3+h9q14gbimMITaL0xJWORemAGpo6dxZrA89aU1gEe5LT+Dv8MyZ+7Lxgv2c2Xk3m9N4+3pF+Hqg2Jx5xrbyKCqBvL1qqor0Mov5wd/jPZ89Tj0sxjCrY7tu3ok2rHqfeK8NUc02aVFmNPs237+OhuLjHOdjW37r0SuZfBWhm7zxZC4+bHzQuq483Bl6zWdnegIacyPqEn54cSTf+mbFrbd57kSpV4SRC8mQMvUuvme+bHuxXd1WWNOLulIXA4+7GA/1wZMn8OflgcOb964rYWr/amfuu5mhv5crF+jXvh3eIe5vtnnL8tVJKu8mmHvzPncGucVw0ivx3Zh9ztoMbXrvl18uGMLNG55g2fju+i3riD/CZd7ug4esI7eihz7eOrdEv6Evf0GvjCqshl/G0EV4xYagRQU5mbZnLuOEZ+GHHbYPN7bp1/wzd4XlZxkFVUxvuoK6XoMYe1A5VPTh8Zrl3PfwQ+SXzWX+whPgfx/DH+frG5wSOm6GlluCatxlO12pbMagGu8QOYes/gBafoC1bwUuP+PfzkwHv/Qx2P4eNO6CHsGFMUsquN3u13v0mBgjG9exKXdl8DYO2Dr/IervM8XeMJQ0vq0YzIrm0+nV0JNzjpofuN4pr0O+qctz1yFw5H36UKZrvYU85dEfVg68ju//fgsFX7/pO5D+36pNlsO/zF3W2981TIL5N8NlhrgKi+/Ru7kqj94N29hzoqQeZlwGdx8ddIyNbQNYt+cg3murD12IGDAbTngObtJjPPSqKoDvrFeNWf/ZMP0S/XVeOfz4DRyyDu5bht3KrKb8LuT88EXMSbhzn4dY/Io3L1gNlzA6/a3wn5u8Ou8lRt/v7TG05GEoqSPo7zr5VWe7iq/apHflzi7S43Ps2AJfvgN/+7/gdSefC/vqcUCqi3I5d+YA5gzW89fZM/rz7x5vMfB2vZLyz61TWXvMAXpeB8Y23sCVWb9l34zovpNQmrUMsnuMheFHJSb4s5WsfP0aCYl78gh3nCFHQPP3UDeS5z7N5rqHXuaAgV3ho9CbxOv+kX/grxtfJ6OthQkzj+AIYP2xo1FK0afa8PATTwvxqtesK83NGibBoEOg9Dm90uKLt6B2WOzHtXLCc/6yzFmb4Vf+RqfRjTeSrxoZpTazvWwot584G9BneH3ynS+CGu58FT+tbdF9Ny39DiRr88OBCzPz9HJerKZfop9LFabGiuUv6OfXE0/wJeF7eT7X/yesfrMrU7P/zVU2As6P2H8RvHkaoM+WdVfOYWz5sYArsm6K+c8wy1+0nqe2eThwexm7fmyh97hfoxXtYFyXwfBQ4LqapizPrwObLuHhnDWxJcATY28fq/v9Ka/D9cZJMELkm/p92O/D+WynTI87E2GoWKxUhHP60oLzmLDvAZQVFRD3HJinvQk3TQv7HHH14Ac5PVVmcJp7DYw/NXhIaiSnvuHvDX7DqIirA3q8vzsPD/153Uj34+ONXKrfDx9YHnHVaA31xcyysvoD+H473BhjkPPT/gXZoSsyu5TksnR8A+tfhuPzruH5/5Xz3d7HcPohnSNItFQAxcupmtEif+taRWEOx88y9CrKLtBv0l+85R9nahxv7SsE7WmO7djxxhHKK9X/2fQ/U0BRo6qiHM5fMo8RPcrAe7H/IbuSZ9pGcmiGRy/AGAsx5gKNgSqs0Ssg7CjpDrsSG/TYjvF9KuGpzezb1+FYD944C/XlH7L1mx/9y0siPPTalVvsSMvUR54GAHbgXjyi+sGT4T7TQkPLQ05mBk+0jeHQkjrIMbX4hMp/ffe33t/IJeyo2Z+CmwcGLq+0LsRpoQphVf0h2xScOq808GHZuG3PfWFgcIBZ0Kd0PuukVfStKQz/nFvnL5zeu2I8WMe0jl1+uf/7LK7VK4CyopuGftuI1fT62+qYk7B45mR4xfvG+1uP61XB3z+yKJiWRtEjTylGD9kb7ve+N/XqbP/iqxzu5WjMV7XD9X+DFwRUAGX6hoDVjQqIs7Ryij9vnzzVnD9VQEyrLyl3NC6Up/sYOO5xx/YXk5pB8NmrCT5omBNQKRitB/pu2baVj7WujHL5gWjegQcx78DA64Z14OU4KoAsYn5Z8j0w+65DTlf+QGBZpiiwx9N2SkGDT7Uu9MkobF+vJC+Lwy1mC/T1oou2biyrywAwVwCV94qqjBUkI8u6ItXmd/h6Wx/e63oIO958j4pxR9rapqooR7+/aW1oKLKzsxyf4TYzO5fpU8YT2E89dAW61dn1sZb4qagt7/d2e5/lFDJv+jQm9a2EmlJHk2VknoTE7Kv6mUwZ69DMsWUNeqNPmAqgM+ZPceZYTsjKjS0uXaQYXr33gy1/DVxmbmA0G7Iw+nRESyl3rreRFFTq/+r3ga2vRF7fzEYs2lXT+vDfXT/yi4P345JH3+XouQMhN1WG7LpLKoDSScr0j4yPOZiqb5xmca6b2TU1g4CN6F7masC7R1ZN4psfYqw4TIDhPco56aDJ/Ob5LfBOAg9sqACa3K+K1dP7cfS4Bkd23b3KUJllowUxsF9UmHxqDkhpfPIIc21oQ0WetcOkPJaZASOK//rl2HALSOCwnyRSkIk37po5IG8YmabeiPesGEevDfdCmAmcopFpmgwgOQx/Y6Lygs38O6JHKQCzBndJ7HUxlATEiEgldjrjnnVAf06/6w29IiReLpft7jh+LFu274YnrT9vw0Ndmd47tL4sikp5b764dtEIbnnpU36MsHrUoogPpgF10aQ90YJ+49C/eXCFvPPCzW4MsHZefEPYhAWLSQAinvtp8twXnnv3l8rCHH57tN4bK9S09OmqE5Rw04RvTKK5B0IHtGnN/pFXMpg9uCvnzRrAOTOjbT2K4sJonkqwOkGzziRZSX4WPSujGPsfhx1ahLybX8mg2sDeYZkZmfSuKuTKKAISOsOfdzwexappfW3He4m0P19cG8BWD8Lv8Bda32/ztjRbDTs1x8kxtn6EaV2MKjaCsUeOx+L7iDIeWOC2hjT6zj9f/Bc7U32iTwkbqxuP9PYs8M3i1nVYwOfNeVHMYmO3V6UvlobTsUxsainpyUeat8Xcava6ED68bHbA+9EN5VR0d/CaafrukyKWGZeilWW69obp0WrUp7qIT9bOYdqAFIiPBFHlnZhVBk+5nRDlvfnNUSMCFl12aORhiYcMr+OTtXPIyzY9SBeZpkMvsjHk08UYHAAT+lRyTJgGjkHD9+HAIV3547KxHDk2ip6PtfoD1dwhdeRmZvC95vBEFrmltlfVUNS6GSfFaQ5PWe+0oHwtAkWRN9tZ3fciNT7YGT7b0VlVjPl0ssYHJ6X2FSbdnfU+7P4q8noAc6/Wx3Db7SY69UJ47lLrz2qHw6TVcJe9rrwhnfRK8DSXqzbpD6JfvRtys4rCHDjjHWj81tZhMjyKFZNNBeP5t9gYghHFhWH+TbDtdX0bldEeDFU4Z0bTL6lR3/DoWTPh8bNhy7P+D7MLoftY9gK+OWUL5dfrv3dLouqol7+gd5Nf541XpDx6bIpYx/ibGVtpMrNh2dP6ud8nfGVobUkeG7QufDB9PR9+sYvr/1HJksPmUznEYkp5c0Fh9AneB0rlD8R95rvwr7sgv1IfW/3XnzGgttT+33HqP/3XrNPfgi/f1h9ofuMdM33IOvi9jcDxRsc9CZ++BBNO8y878FoYuQS6jYRjH/cPXzj1DWhtgW+2wJ+8XZ+PfVyvSGneTd4Xb0d3bIPZ3ng3nPoGvHxdezyccb31IWCfL3yahqz/QUsjfPdf652c+k/Y/CT871PYuM7wgSHWk7GibthifahJb4eC6Uapas5F7Mh6l6+7nUilnVg7Z74LP3xj/dmkM7l+czGj+tQx7gUb95YRS+D124KXDzwEpl0YeXu3lPXU48xNWq2fK+BOK+uJLwYHuJ5wOrS16RWCrU32Jpg47kn+9MwrvP1dAZfObtCDzb+yDt57pH2VxmHHkvvGrdGl7+Qohr91HwvTLoLhwTHG4nLck/DB0/rwr+FHObtvO45/FsoamGma2npUQxyzIp64AXZt1V+f8Jx+7Xp9PTzrjX9mrpBf+ijUBlZAxeWkjfCvP8PQRdafZefDNYHXgry5V4JSTOxbGd2xjr4fvv4QlCI3y8N2yjix+QxuzLqGDBX7g9s2rYK6JbdClzANA6e9CV+83V7Ozcq27rVquwFk5d9hnfd8POV1d64Jy56BW7xlgqxcOO4p+HYbPHQqNDsddC+CcA/WR90f+rNwznjHfliGZc/ow6G+3QZjrWOGprST/xG6nGBlycN6nLPnLwtcbizXDTtSj9Xniy1ZNwoGzI0/rXa0tQYvW/GSdWB5p+Va9FDvOwM+CNFlEfQ4nCIsqQBKlrwyvebWbu1tdj70jDQ7jPeGpDzWJ4zPsmei6u4fklWrlG9ss7kCqKIP7PjQ/76kG3GFdRm8II6NLeQUQa/Jzu5TBLj91Lm898W3UNktuMeDYaaw8opKvus2laLPnqN/bYTxz07xjW/2ZEFbi34O2Y1NYYupsGgzPtLFBw1iQt9K+g6tpY+m8ebMPZTkh+iJZB4C5vEEVzAV18LEM/TXm/WbZ3VxFK2ixmtWcVf9X0AaYqiw676P/s8oOx98s5wZg4j7emX4ekB5MgM/3/5+8P5HHgubonj4zSmEqRe0v101tQ+HDq+jvjwfaAi/bXkv2GclPHG+9efm2A9KRawEdJPKyOKMWVF05S+uDR2k2pPBKSecqL+2E692rwOtK4CmXhj+/uU272QMZBl7K7jwsGc1M5snAyafHd1+uu/DouNM50/jroAKoNxxJ0A0FUDFddHHo9o39thbIVldGxKpm78h6JFTJjL3+r/Fv8/CKn/wWF88o8wwPWPCzfYYi+oBsP/FoT8LokznQhTyyqBen855/shuPPf+dp5sG80trbNZnvkoAFe2HM7ZWXdHtdviouLI5bWyhoC4mK0qk7jOY2PMF5s99aJWb5r62hds+/3H4a3oviNX9YmxwaLEouxnpahW/y7M30dHUlQTFEcsLF9cwKGL4c07/cuNZapDbtT/H7kUNq2H4UcmbgiY775oFK4C1m1DDg+uAMrMgz3egabmOJwiiAwBSxo3TlpvjX2khzCnejUIEYWBtcXMG+G9+be2hF23KEsf2z+md4KHOPhupk7fVGPcXV52BgcN1R+4lVKhK38g+sqX9vgJHXAMeajfJ8OilTfO+C0ej/JW/ohOodX70Ggc4tjR4yxE202+M8S/itLedXql5KIxkadAj5oxlk2q5bWMeIY++80dUsvHl+tDR425sTWGx5DCXJsx6Azf5eB6695Lty1xsHdVOkm1fNhpmK7VVtdiX2OfVa8ct1hVACWM3bwow8GiIXf5RDI+nLjVggBQ2S985PhkXNitYpa4odDQo8rqYVCkBvMUqOZeBb738c5QF61KX6u30+dIAs4586xgkeR44y2VOvhAYx4S6hrv91lh6qVldd0LNXuOXB/cUxp59o32/GcWbrx/IvjuVcZeD5FmYkk15h5UWVHGPklE/KMOaPMls7j0EBtDJaNlzF+JiKcUjSrnYi8pb9nzK81/X/+aElozo7t3Kbv509CzqrCml+V5HNdwPjcZQxwko8ye6Ngqxr+xM1U+me+D5hhhVjOh+mbrjSXOUKyivYc4yW5+8E35nmrX0BQlQ8AS6ZRNemyI5u8dmSI7SEYWHHmvHkisoFJvVWrbA/VjYetGvWBtvGAsfcy5ab9DyS2FyefoY1fffUjvouemw2/3xyDpaIX2zmTqhdBlCNynT2vMAb8I/Hz2VdB/VuDUk6f9S4+dsOFXgfGDnHT0X+C/b+hxepzkVoHm6L/oQ7J2bIm+krVhAiz4PfSfHXndSI5/Vh86VdVfPwcr+8ONY8Nvc9xT0PJDbMfLyPRf64y6j4XRx+uFqpFL4MWroPc0Pc8A9J+jdx3OL9djvfz4DXz2WsAQRGekeAH2hGeDAxA7adlT8N6j8OiZodfpOgR6TIRPDcNq+s6wNXWrqxb+Cba9Flj5vNdBoddPRQ0TYcbl8N3nMGqZXqFzyDr4y0r986oBMOMy+PF/eqH5T0cEbn/47YlPcwfgm5HUcUMXw4Mn669HHadX4N1/gjvHisbie/zD1Bxy/0nj2fB+L6iaCMrDVYMPg+9OhY9f5Np7n+Kjtq5cm31j+/pnNK9kbFfFwqEV+tCjXdtshEPwKq2HhXfC7i/1MmhGNsy/hX88fBNjmr3TSueVwqK7gs8BK6tegx93Rv03x+TgXyfmOJFkF8K83+mv/7zYveMEVDil+P3TCb4yU3aBXn7zmXI+1AyCvgfAxxv0a/fKv8OeRv8640+Dku7Oh8IIp3ov/b5w9zH6+xHHJO7YZksfs46vVL0XfLIBDrwu8WnqgKQCKJFKu9sIXBynvgf4Xw853P/aqsdRwwR30wJ6fI5x3oJNIi4Yvtb+yn5Id8AUlpmj37x8FUDmGAM5hTDw4MBlZT30fw0T+e6nXShSjk8qq8dmMJ5Dqa73VP3/WGeJ2Xu+M+kwxMoI+t3MSur1irzirvFdD0P9TnN+5X998A2w1RvMtm4ULLozcN3SeutYLE5LtRZNt4PcF3WB0cvCVwCBHgfIWAGUyAJtKAUV0G9G4LJU+/3sGHdS4Pthi+Hzf8I/fqfHxQoXxyPRPS87O2NgeE+GXnZLhQqgflEG9LdhRPcyRnQvAwz3rJJuMGwxV/9Z77l2Lf4KoAfaJrG7pIaF++pTNftmFrNtwJzA94MX4HnqTmg2LOtvMamCFUfjAkYQMONvEq4/vmtebknwd5ioY6czY5nJGBcpM9t/H9zLG+DZGH8K9AawIYe5mz4rxrJd3agEHtiUHxomwFv3et8YnvN8Q2nTYLbsRJAhYEKIDkd1tMo9iamRPL6A963N4dcTCaaQSvpE8xWk5XsXqalrSXDAaadHIw1t6GBDRDpDhUiAzvb3dkDJzpNWx/ddKJKdtg5CnkqEO3zjRfMSPL7aF9ejoFqf6hpM40HlwpByfON2o/Cu5nJPOqd5nAmkmRZ8U197EtQB1Ze/Ejkk1NyDItwsP52ZOWaUVbwD4Rxfvgx1zZWeP8ljjlvRCc+Fh1dN5OFTgmc961LibFywrOIETy4RL+N5maj7mK/MYo7XmAjJOKaITiKvT1YVOr4h7MZnzALvM5/boUbShAwBc8PxLsUn6Uh6TdXjuAxdmNjjlveEg27Q48dkZOmxEPaeB1c06J8rBYvv1bu13uKdJnDRXYlNo/BbcGv0XbqBqwtO55zvf8Uwz5bIKwMsexr++nOY/gt492E9SG1Zj9CBaJ0y60p4/Ozg6dI7g+UvwO+8U/UuuFXvnltQpQ9X++Dp0NOJO62yLxx0vTOxjuyacBp8v13vuq21uT/kKlUteRg+egE2XAXAFwV70eX7d/XPPJl6XI7mH2DoEfCvexI/1CCSY59Ir9bESWfqD5PDTLE8Tv6HHoeiZhBs25SctHV2x/8VPnvV/37lS/DfN5OTlqMfSHzjHTC4W0nQsmsXDmPGoC4Wa8dhygWw8z8wZnn7ot0ZJRS27uLtgWew9+TD9WHKba2w/T13r0uL7gqMe3bcU8EzLk27SI9ZpxQMsRGryAlFNXDwjdAnQdNp+66zE06DcasSc0wRvXk369epQfMSeFBv3tj3HH9Msn4z9GfMYYv1oeS5JfrzX+9pjsctS1dKS3Skd2DUqFHaa6+9lvDjuu5i783r4l3JTYcI5vttVAb89JvAZfJ7dTi7m/bwQ9Meqotz+aF5D29dNpmxvB16g2T9xu88APcs1cdOd8bAqnKOCQjMB77XP92ZXpUrQghnXGyoCErQvePV/1vA6G+fZtOItYw8aGVCjtnhuHk/v2E0fL1Zr4x2cOY5kQbuORbeuR/m35IacQI7EKXUJk3TLAM2SQ8g0bnIA0daKMzJpDBHv3zlZ2fSq7IAvk5yooQQ9sm1WAiRIpTWqr/wSGQMIVKKr6yQhA4r6UyudE6TYK8pTh460lFVRQLjuwghhBAibRQX6b1bKktcHhbe0bkVX8U3c5PKcGf/ogOT5zY3SA8gJ829GrqPT3YqhJVlz+gxf4ytzov+LMFZ08VBN8C9S+HjF5OdEmG09DH4YUeyUyGSbdkzsPNTAHYteZ7dH79KXZKTJIRIUQdep18v+tmcnt0BfY++mp3P9abHhMMTdswOZ86voGFfd/Z9xB/hrXugorc7+xdpQHoAOUkqgJw06rhkp0CE0mVv7wtDBVD/WUlJinBBQYUecPbrD+GGThpwNxU1TEh2CkQqqB+t/wNKeg6npGf0gd+FEJ3EyCUJP6TKK6N09kUJP26HMvp49/ZdXKsHgBbCTIaLu0LGK4nOwTd2VC4k6S27802dK4QQQgghRNqSGECOkgog0Un4LhxSAZTWsguSnYJAvphgMq5dCCGEEEII+zxZ+v/SgO8oGQImOgfpAdQ55BTD5PNg11YYsQS2boQeSYzL1X82jF0Bk1YnLw1CCCGEEEJ0NDMuhZxCGHhIslOSVqQCSHQS0gOoU1AKpp7vf999bPLSApCRBbOuSG4ahBBCCCGE6Gjyy2H2lclORdqRIWCic5AeQEIIIYQQQgghOjGpABKdhPQAEkIIIYQQQgjReckQMNE55BTD8KNgxNJkp0QIIYQQQgghhEg4qQASnYNScPCvk50KIYQQQgghhBAiKWQImBBCCCGEEEIIIUSakwogIYQQQgghhBBCiDQnFUBCCCGEEEIIIYQQaU4qgIQQQgghhBBCCCHSnFQACSGEEEIIIYQQQqQ5qQASQgghhBBCCCGESHNSASSEEEIIIYQQQgiR5qQCSAghhBBCCCGEECLNSQWQEEIIIYQQQgghRJqTCiAhhBBCCCGEEEKINCcVQEIIIYQQQgghhBBpTiqAhBBCCCGEEEIIIdKcVAAJIYQQQgghhBBCpDmpABJCCCGEEEIIIYRIc1IBJIQQQgghhBBCCJHmpAJICCGEEEIIIYQQIs1JBZAQQgghhBBCCCFEmpMKICGEEEIIIYQQQog0pzRNS/xBldoOfJrwA7ujEvg62YkQwiGSn0W6kTwt0o3kaZFOJD+LdCN5WqSCHpqmVVl9kJQKoHSilHpN07RRyU6HEE6Q/CzSjeRpkW4kT4t0IvlZpBvJ0yLVyRAwIYQQQgghhBBCiDQnFUBCCCGEEEIIIYQQaU4qgOL3u2QnQAgHSX4W6UbytEg3kqdFOpH8LNKN5GmR0iQGkBBCCCGEEEIIIUSakx5AQgghhBBCCCGEEGlOKoCEEEIIIYQQCaWU6qWUmqaUykl2WoQQorNIegWQUqpEKfW4UupppdQDSqls7/JblFIvK6XWGNatUUptMLz/mVLqee+/95RS54c4RpZS6hHv/o4zLN9LKfVghPSVKqVeVEq9pJSaZVg+WSl1U4RteyqlXvVuPyLUslTaVsSvA+fpLKXUBqVUXYTtA/K+Umq6Nx0vK6WOD7Od5OkOKtXztHc9x/Kl4bMTlVIXR7Ot5OnU10Hz84OG436hlBoXZtsjlVI/NS3r6d02ZLlPKTVaKfWGUuoZpVRDqGVObyvil+p5Wik1XOlljhd9eVMpNR1YBxwAPBZm2w5XDhfx66B5erRS6gWl1Eal1LII25uv8XOUUn/zbjsnzHaSp0X8NE1L6j/gJOAA7+t1wEHAPGC9d9mNQF+gDHgCeD3Efu4B6kJ8diZwsff1/UAR0Bt4BHg+QvquA5YCGcDjgAL2AZ71pTHMtg8BU4BC4C+hlqXStvKvc+Zp7/ILgdMjbBuU94E/AvlANvCRG/lS8rTk6UTmS+/yamCbL01O50vJ05Kfw6QvZBkDKACexHvdtvj8UOBlc75Fv9aPjHDc14E+QD1wa6hlTm8r/zpFnv4tUO19/Q5QAqwCSrzLXgNyQmzb4crh8q/T5un7gVpvXn03zLZWZZYX0csrBaH+lnjzpeRp+ef7l/QeQJqm3ahp2tPet1XAV+gZ8W7vsmeBiUArcATwrXkfSqnRwDZN07aFOIxxfy8Do4DvgPk2krgvcK+maa3AFqAB2AqEbFE2GKhp2vOapu3Wk6kyQyxDKXWoUuroRG8rnNcR87RSqi9wBpCtlBoVZtugvK9p2lGapv2AfvPYbfgbJE+niQ6Qp23nSwuh8tEv0QuYxr9B8nQa6Ij52eAkYJ2maaFm8HgNuMCU1qOBOmCiUqqbYflKpdQB3tflwB5N0z7UNG0rUGO1zIlthfNSPU9rmnaipmlfKaWygEzgB03TbgCalVKLgY81TWsKsbntcrhco9NHR8zTwA5gINAT+DrM5lb59zv0CvMhwMeGv0HytHBcyvzISu/OXKZp2itKqRPQW15BP6H7aJr2rXc9q81PA3zd7x5Er4X1uRO9NtW4vxpN054z7k8plYfesmD0f+gFmN2mbV9R9roz7zS8/h6oDLHsC03THkjGtpH+ABG7jpSngZOBK4E7gN8ppdZomvZPc6I0TdsWJu9fCvzKsK7k6TSTqnla07SH7OZLCzsNr78HKpVSA9ALcy+hFxABydPppqPlZ2/BfC4wNdTfpGnaVqVUb9PinwHHoT9APaCUmqhpWpOmaesM6xjTC5AbYpnvODFvK9yTynna+/pM4E5N01q872uABcB/wvxZtsvhco1OPx0pT3uPcSjQgt4byFKIsvSD6D3dKoC7DOtKnhaOS4kKIG9L0fX4a1x3A3ne14WEiVWklCpF74K3BUDTtIMt1pnj3d8uQrQGa5r2I4aCvmHbCw1vw6bFQpvFtlbLUmlb4YAOmKeHA8s1TftRKfUIMAkIqgAKk+ZDgUpN024Ls5rk6Q4slfN0mOPGki+zgYvQu5oPj3AIydMdVEfMz+ixUl7QNK0t4pr+dFQCX2ma9rz3/UdAf+BfplWNfz9AcYhlVuLZVjgk1fO0UmosMBvY37D+J8A8pccf7KJpmtWDZ6vhdUcphwsHdMA8vULTtLnezx5SSj2qadrmsH+kvm4RMFXTtEXe968ppR7XNO07i9UlT4u4Jf1HVnpQr7uB8zVN+9S7eBN6tz6AocAnYXZxMGGCx8WwP7N3lH9IzBDg03Arm+xUSnVRejVyb2B7iGWptK2IUwfN0x+id1kFvQus7XyulBoJnIvewhyO5OkOqgPk6SBx5Muu6PF/HgSuAZYqpRbY3FbydAfQEfOz1+GEaVUOYQeQr5TKUfpQhUHAZ+aVNE37H1DhXS8fyLJaZnWAeLYVzkj1PO3t7XAjsNjX+0fpgc37KD0weS567wMrHbEcLuLUEfM00E/pQctL0a+1oYbqmmUAg7zXy27owxz3hFhX8rSIWyr0AFoGjAQu9PZMWAf8BdiglKoFZqEHywplBnBVhGPcBjymlJqEPjZzYxTpWwfcopTaCOwOM47Uyq+BB9BvVs95uwcGLYP2lupCTdP+kMhthSs6XJ5WSl0A3KCUKkAfe/xoFPu7Eb1192H9/sHBmqbtkjydVlI9T1uxzJcW65nz0UZgMIBSagowRdO0e73vJU+nh46YnwHGENxzJyxN0zSl1M+BZ4BS9GDM34Aexwf4UPPH2bgdPSAowB/CLItrW+GKVM/TVwDlwB3e6/GJwCXow3BagN+E6O0AUZTD5RqdVjpinr4CPSB0IXCLpmkf2NmRpmk7lVJ3o1fOe4DLvD2PJE8LV/hm/0k5Sqky9O7OL4boEhrt/mrRa3mfDPEQEG7bPsAw4GEtdJC6UNsOBXoAj/i6bVstS6VthTvSJU/HQ/J0ekmlPB3ncWPOR5Kn00e65Od4KKUmAHmapj0TbpnT2wp3pEue7ojlcOGOdMnT8ZA8LeKVshVAQgghhBBCCCGEEMIZSY8BJIQQQgghhBBCCCHcJRVAQgghhBBCCCGEEGlOKoCEEEII0WkppYYppYaZll2TnNQIIYQQQrhHYgAJIYQQotNSSi0F0DRtfXJTIoQQQgjhLqkAEkIIIUSnpJS6HDjU+3abpmn7eZc/r2naFO/rTcBXQDPQBfiT9996oAR9ZqLLE5tyIYQQQojoSQWQEEIIITotqx5Apgqgd4HRwFvA/sAaYBfwhqZp65VSG4HZmqbtSGzKhRBCCCGiIzGAhBBCCCFC+1LTtN3Ap0AroID+wEql1PNAAVCbvOQJIYQQQtiTmewECCGEEEIk0Y9ABYBSSmn2uka/DzyoadpzSqmjgG/cTKAQQgghhBOkB5AQQgghOrOngXlKqZeASTa3WQus9m4zE/jSrcQJIYQQQjhFYgAJIYQQQgghhBBCpDnpASSEEEIIIYQQQgiR5qQCSAghhBBCCCGEECLNSQWQEEIIIYQQQgghRJqTCiAhhBBCCCGEEEKINCcVQEIIIYQQQgghhBBpTiqAhBBCCCGEEEIIIdKcVAAJIYQQQgghhBBCpLn/B49bvm6i5LskAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd_pre = pd.DataFrame([pre.reshape(1,-1)[0],test_y]).T\n",
    "pd_pre.columns = ['预测','原来']\n",
    "pd_pre.index = test_y.index\n",
    "pd_pre.sort_index(inplace=True)\n",
    "pd_pre.plot(kind ='line', figsize=(20,8))\n",
    "plt.title('2017一月份北京市关于pm2.5对于AQI数据的预测')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bdb901d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '2017,01,01北京市关于pm2.5对于AQI数据的预测')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ut6T6R+xn/XWXWiyEeBdMCNCXwNRuvhqGQH+vPQefDWPHfTpMAjDsNt4Lo0y/RZj2M98CE2r0cQB/TkTftuhxZDAYjEsdTDgZDAZjgyGE+AIieuu6bGfJfXgYTPuOsw1usxe0+mgUqyKc02Dtt7Bq8SUBIcTWDOV4mW0/sbqYIIS4NkzOtY8l4YJE8Pg2ER22sW8MBoNxqYAJJ4PBYDAYDAaDwWAwWgHXcDIYDAaDwWAwGAwGoxUw4WQwGAwGg8FgMBgMRitgwslgMBgMBoPBYDAYjFYQz37Kcrjmmmvo0Y9+dNtvw2AwGAwGg8FgMBiMFeA973nPGSK6dtzfWiecj370o/Hud7+77bdhMBgMBoPBYDAYDMYKIIS4a9Lf2FLLYDAYDAaDwWAwGIxWwISTwWAwGAwGg8FgMBitgAkng8FgMBgMBoPBYDBaQes1nAwGg8FgMBgMBoNxuSDLMtx7770YDAar3pXG0ev1cNNNNyFJktqvYcLJYDAYDAaDwWAwGA3h3nvvxfHjx/HoRz8aQohV705jICKcPXsW9957Lx7zmMfUfh1bahkMBoPBYDAYDAajIQwGA1x99dWXFNkEACEErr766rmVWyacDAaDwWAwGAwGg9EgLjWy6bDI52LCyWAwGAwGg8FgMBiXMLIsg9ba/57nObTW2Nvbm/iaO+64A+fPn1/6vZlwMhgMBoPBYDAYDMYlhLe85S34si/7Mnz1V381Hv7wh+PVr341vvZrvxZXX301nvvc5+K5z30u3v72t+NLv/RLcfPNN+N5z3sevu3bvg3f8A3fgPe9730AgN/4jd/w/18GHBrEYDAYDAaDwWAwGJcQvvALvxA/8iM/gr/4i7/Ad3zHd+Drvu7r8KIXvQj/5J/8E7zuda/zz3vjG9+I8+fPI4oi/Nf/+l/xu7/7uzhz5gy+/Mu/HM94xjMg5fL6JCucDAaDwWAwGAwGg3GJYXt7G+94xzvwdV/3dbjlllvwtKc9DY961KPwohe9CE95ylNwyy234G1vexse97jHAQBe9KIXYXd3F0mSoNPpNLYfrHAyGAwGg8FgMBgMRgv4ydf/Iz58/8VGt/kpN57AT3z1k6c+53d/93fxyle+EkSEZz7zmXjOc56Dr/zKr8SxY8fw9Kc/Hffeey+e/OQn48UvfjGe+MQnAgCiKMKJEyca3VeAFU4Gg8FgMBgMBoPBuKTwghe8ADfffDNOnjyJpz3tabjxxhsBAKdOncI111wDADh+/Dhe//rX4zGPeQyICFmWIY5jEFGj+8IKJ4PBYDAYDAaDwWC0gFlKZFsIay9/+qd/Gu9973txxx134J577sEjH/lITyr/5E/+BB/72McQxzEuXryI48ePe/LZ2L40tiUGg8FgMBgMBoPBYKwVoijC9vY2HvWoR+H06dPodrt4+tOfDq01Xv7yl+M7v/M78U3f9E14whOegDvvvBPPfOYz8cM//MONvT8TTgaDwWAwGAwGg8G4xEBEXsl88pOfjL29PTz72c/Gt3zLt+DZz342XvWqV+EZz3gGjh8/jh//8R/HS17yEvR6PbziFa/AE57wBNx6662Iomjp/WBLLYPBYDAYDAaDwWBcQkjTFM94xjPwghe8AHme43u/93tBRPjVX/1V9Pt9PP/5z8dLXvISPP/5z8dDDz2En/iJn8BNN92EH/uxH8MDDzyABx98EJ/1WZ+Fpz3taUvvi2i6KLSKpz71qfTud7+71fdgMBgMBuNyw9tuP4Pv/z/vx80/9EzsdHn9mMFgMNYFH/nIR/CkJz1p1btRwn333YeHP/zh/vfDw0N0u92FFMxxn08I8R4ieuq457OllsFgMBiMDcQnzh7g9N4Qu/3mgh0YDAaDcWkiJJuA6dHZhF22DphwMhgMBoOxgdDWoKR1u04lBoPBYDCWARNOBoPBYDA2ECcvfgyvSH4eKhuuelcYDAaDwZgIJpwMBoPBYGwgrjn/fjwnehdw8NCqd4XBYDAYGwSlFNrO8QnBKQMMBoPBYGwi7GRBq3zFO8JgMBiMdcOrX/1qvOxlL/O1m4PBAL1eD4AhnH/0R3+Eq666yj//F3/xF7Gzs4Pv/M7vbHxfmHAyGAwGg7GBINIAmHAyGAwGYxRRFOH7vu/78KIXvQgA8Lmf+7l4y1veAiGEf853f/d349Zbb4UQAvfffz+klHjNa14DIsJTnvIU/NIv/VIj+8KEk8FgMBiMjYRROCnnlFoGg8FgjMcP/dAP4ZZbbsHu7i6e9axnYTgc4nnPex5+4Ad+AC9/+cvx27/923j+85+P3//930ev18OznvUsvP71r8d3fdd3NbYPTDgZDAaDwdhACFIAAK3ViveEwWAwGBPx5z8KnPpQs9t82KcBX/HSWk/d3d3Ft37rt+K6664DALzvfe/DxYsXAQDdbhdPetKT8HM/93O44YYbAAAvfelL8d3f/d3odDqN7S4TTgaDwWAwNhAu70ErVjgZDAaDUUae50iSBESEq666Ctdccw0A4MSJE9jb28Pf/u3f4id+4ifQ7XaRZRluv/12CCHw+Mc/Hj/0Qz+ELMvwH//jf8RznvOcpfeFCSeDwWAwGJsIq3AS13AyVoQLhxmSWGC7w9NJBmMiaiqRTePUqVN48pOfjMc//vF4xStegfvuuw9SStxwww14wQtegC/5ki/Bl3zJlwAAvv3bvx033HADzp49i0//9E/Hy172skb3hUcIBoPBYDA2EVbiZMLJWBW+/bfeiU97+BX4ya/91FXvCoPBqOADH/gAnve85+EpT3kKPvMzPxN33nkner0ehBD4hm/4BgAmrfb7v//78ZjHPAbXXXcder0e3vve9+Kbv/mb8Qu/8AteFV0W3IeTwWAwGIxNhEup1Uw4GavBuYMUZw/SVe8Gg8GoYH9/Hx/96Eexs7ODb//2b8eNN94Irc094/jx4/i6r/s6fOADH8Dnfd7n4eTJk/jxH/9x35fz5S9/OZ74xCfi8Y9/PN70pjc1sj+scDIYDAaDsYnwCifXcDJWA01FLTGDwVgfvPnNb8YLX/hCfOhDH8Iv//IvY29vDy972cvwmte8Bs94xjNw8uRJPPrRj8ZLX/pSPPvZzwYAHB4eIooiAMCLX/xivPCFL8RjHvOYRvaHCSeDwWAwGJsIq3CypZaxKmgiaGacDMba4Su/8ivxlV/5laXH7rjjDv9/V7vpyCYA/OAP/mDp+Y997GMb2x+21DIYDAaDsYlwhJMttYwVgQhMOBkMxkww4WQwGAwGYyPhLLXch5OxGhARW2oZjAmgS/TiWORzMeFkMBgMBmMT4S21XMPJWA00mX8MBqOMXq+Hs2fPXnKkk4hw9uxZ9Hq9uV7HNZwMBoPBYGwiXGiQZoWTsRpooktuQs1gNIGbbroJ9957L06fPr3qXWkcvV4PN91001yvYcLJYDAYDMYGQnANJ2PF0FzDyWCMRZIkjSW8XgpgSy2DwWAwGBsIsoQTnFLLWBkITDcZDMYsMOFkMBgMBmMKPnpqD5/+k3+Fhy4OVr0rFThLLRNOxmrANZwMBqMO2FLLYDAYDMYUfOLsAS70M5y6OMB1J+YLSmgVrHAyVowfU69A/+LjATxt1bvCYDDWGEw4GQwGg8GYAm0lnLVTclxoEDHhZKwGT8OHcN+QU5IZDMZ0sKWWwWAwGIwpUJ7YrRfjFHAKJ6fUMlYDCSrOQwaDwZgAJpwMBoPBYEyBWluF0070uYaTsSJI0hBrthDDYDDWD0w4GQwGg8GYAkc4103hdJZaJpyMVUGAioUPBoPBmAAmnAwGg8FgTIEnnCvejyoEE07GihFBQ67dlcFgMNYNTDgZDAaDwZgCb6ldN0+tt9RyDSdjNRDQrHAyGIyZYMLJYDAYDMYUuNCgdeObsGEt3IeTsSpE0BwaxGAwZoIJJ4PBYDAYU1BYateMcVoiLFjhZKwIAmTqOBkMBmMKmHAyGAwGgzEFlKf4OvkW0NpJnFZZ4j6cm42HPgLc/Y5V78VCiMAptYw5MNwHPvTaVe8FYwVgwslgMBgMxhRcf+YW/Hznf2L7/K2r3pUShFc4mXBuNP7uvwFv+MFV78VCENyHkzEPPvJ64I/+JXDh3lXvCeOIwYSTwWAwGIwpECoFAJD9uTbg0KBLA9khsG7nVg0QEddwMuZD3jc/s8Fq94Nx5GDCyWAwGAzGFBAp+3O9Jtaudk6wpXazkQ8B2rxFAyJAsqWWMQ+UHavYlXHZgQkng8FgMBjT4BTENSOcbn84NGjDkQ83UqXWRIZwssLJqAudlX9exviH+y7gp/7sw6DLZMGGCSeDwWAwGFOgtW0/smaE0ytLG6iOMQLkg438DgmABLHCyagPlZV/Xsb421sfwqveeicydXlcP0w4GQwGg8GYBqs+rWtKLYcGbThU6lvcbBI0EWLBCidjDniFc/MWWJqG9v2dN+/aXwRMOBkMBoPBmAJaW0utq+HkydtGIx9s5ATcLcBwH05GbfgaTlY43frlZcI3mXAyGAwGgzENaxsa5Go4mXBuNjY0NEhbZV0c0XXx+g/cjwt9JiobDZfGzJZaaM0KJ4PBYDAYDAenPun1IpxwKbUbqI4xAmxoaBDZ60EegcJ5Zn+If/v778MbPvhA6+/FaBHeUstlAGypZTAYDAaD4eEsteuWJshtUS4R5MP1s2vXgLb2yKOo4cyUeY/DlM/1jQa3RfFwltq1iwZoCUw4GQwGg8GYBlrPlFqwpfbSgNpUS609/45A4VR2Vp6qNbsGGfNBc0qtg1c4LxPGyYSTwWAwGIxp0Otdwyk3kKwwLLQyas/a2bVnwyn/R1HD6Q7PMNu848QIoNhS68A1nAwGg8FgMAq4CfWaTQzYUnsJIB+an5u4aHCUCiexwnlJQLOl1oEttQwGg8FgMDyKtihrRgrsJHxlCucDH9hIZW6tkA/MzzVTz+vApdTKI6jhdCpQmm/ecWIEYIXTw53T65YN0BaYcDIYDAaDMQW0tgrnCms4z90J/NoXAXf83dG/96UE1yZiA1Nqj7KG09kPmXBuOLiG06NIqV3xjhwRmHAyGAwGgzEFru0IrZuat0qFc3ix/JOxGLzCuXmEE0dYw6lY4bw04BVOJpzcFoXBYDAYDEaBNU2pXanC6W3G63VMNg65VThJr52CPgvuejgahdP8HOYbSMwZBXwNJ3+PRQ3nZl33i4IJJ4PBYDAY0+AI3bpNDFapcK6pzXjj4BROYOOOZVHDeQSEc0po0AMX+viFv/7YZVMLt9FQbKl18Cm1l8maHRNOBoPBYDCmYU3VPKcsSaxC4bRKxZodk42Dq+EENs5WS8paao8gNEhNqeF8wwcfwC/89W14aG/Y+n5cNrjnncBH/7z57Wq21DpcbpbaeNU7wGAwGAxGkyAi5JqQRA2tqTpL7ZotRbvauYgttZuLUOHUCoiS1e3LnHChQUehcLoazuEYwrl7aMhLfrmkrxwF3v5LwJnbgCd8RbPbVdwWxYEttQwGg8FgbDD+/uNn8ZSX/BV2D9PZT64DT6rWbWKwSkstE85GULLUbpbC6WqHj0LhpCmhQeftda6ZcDYH0u2okD6llgknp9QyGAwGg7HBuHe3j36mcP6woQmTnVivX2jQKi21TDgbQR5aajfrWGp7DhyJwulDgyYrnOpymbkfBUi3o0JySq2HWyC5XGqPmXAyGAwG45KCu5GrhiywYk3JlbPUssK5wahaajcIzmIujmDCPK2G0ymcbKltEKTbSbPR62Wpff89u3jb7WdW8t6FpXYlb3/kYMLJYDAYjEsK7gbe2AR0TRNZncIZrUThXM9jsnFQm6twklc429/vaSm1zslwudTCHQnaVjjXJKX2l//2Nvy3N35kJe99uYUGMeFcAB954CL+7IP3r3o3GAwGgzEGLmAkV83cyMWa9uFcZVuUNDMTxosDTgZdCqUazjU7v2bAEc4j6cM5pYbT1Wo3db0zYMaWNginT6ldD4Uz14RBthpngTunLxcrOBPOBfDbf38XXvKn/7jq3WAwGAzGGFDTN3JH6NYtpdYqS6tQOE9dOAAA3H3m4Mjf+5JCWMO5YZZaHGVKrXYptaPHyIcGXSZK0ZGgNYVzvSy1msar5kfy3peZSYQJ5wJIc821AgwGg7GmcJPT5iy1VP65JihqOI9+wuR6MNKmkaR1wwan1Gp9dCm1kxTOQaYwyMxjl4tSdCQg3c75qNfLUktEY1VzAPjoqT0cDNsjxmypZcxEqjQUWzcYDAZjLeHmnU1NQOWaptQ6rELhdETzcklYbA0qsCRvGHknOtqU2h6GSCsK5/mg9RELAQ2CdDvno1ovSy3R+ORjpQnP/ZW34TW33NXaezPhZMxElmtfI8RgMBiM9YL2CmdDBHFNQ4Okt9QePRHWduIoNkyVWzvkAeFc0wWNiXAptUdAOEW6h3d3vwdfqN9Vevz8QaGUbfLE/aOn9vC1v/xW7A3WQ/lrzVK7ZjWceoLCmWuNfqZw7qChXs5j37v881IHE84FkCrN1g0Gg8FYUzQdxlCQqvUiBK4dxWoVzvU6JhuHEuHcLPJ+lCm10WAXx8QAN9JDfkEJKAKDgM221H7kgYv4wL0X8Ikzh6veFYO2QoNcDeeaWGo10ViF061VHqbtXZPuPnW5uESYcC6AjAkng8FgrC18Sm3jbVHWi1y52rkY6sjVV1+7uWZBSpsGlYV9ODfrWNIRhgZBG2LZRVYKeXEtUYDNJpyOfFxcF4UTl0dKrSZz3lTPHeeOaZdwln9e6phKOIUQVwoh3iiEeIsQ4hX2sVcLId4uhHjx0ezi+iFlSy2DwWCsLZwC0lStvVNw1m8lOtifIybDPjRozUj4piEb9otfNk3hDGo42742yKb59kRaUqTOXyIKpzt8F/prQjjddd30Isia1XC6IbRqq3Ufu5+1GBqkm3XirDtmKZzfAuA1RPSFAI4LIf4DgIiIngHgRiHE41vfwzVEqrRxG1wmJwmDwWBsEtzQ3JTCKdZW4Qw+3xFP4BzZWLe61k1DPtzcPpyOIAvo1lUaYYlKF2mJHOweptjCAF8oP7jRE3encK4f4WxwXNEKnuGtkaUWGG23czQKJ1tqQ5wF8AQhxEkAjwDwaAB/YP/2twC+YNyLhBDfJYR4txDi3adPn25oV9cHmbVzsMrJYDAY6wfVWmjQehECEe7PURNOV4u1YarcuiFPA4Vz01JqA0tt65NmNdlS+7XR2/E7nZciOnio3X1oEe7wXbyUCWdIMtdE4ZzUbsfdQ46CcG7wOslcmEU43wrg8QD+HYBbAXQB3Gf/dhHA9eNeRESvJKKnEtFTr7322qb2dW2Q5ZeXDM5gMBibBGo4NEhiPdW8lSqc3BalEZRqODeNvNtzIBbtK5xkCWevonCeP0xxFS4CAOTwfLs70SIuD4VzHQmn+VkNDnKCUr9NwukO8WUyhs4inP8NwIuI6D/DEM4XAtiyfztW4/WXJNzqGhNOBoPBWD/40KCGajg3w1J7tGTFhwat2THZNOhSaNBmEc6wfle3HHgkbb9SU8NZHKfdwwwnpVGJZXqx1X1oE246uTahQX7Ma/CcDBXONbHUkrfUls9fd+84TFus4eQ+nCVsA/g0IUQE4HMBvBSFjfbTAXyivV1bX7jVNbbUMhgMxvrBTd6aa4uypoST1oBwbhhJWjdQqS3Khs0pgu+e2k7YtRbuLrIRhfPaxJD2aLjJhNMpnOuh/Plzscnrew0tte6KGwkNOgqF09dwtvYWa4VZhPOnAbwSwAUAVwH4eQDfIoT4OQDPB/CGdndvPeEUTg4NYjAYjPWD9jWcDRFOl1J7FO0f5oDACms49XrajDcOAeGkNZmE10VIMqltO7Aeb6ndPcxwVWwIp0z32t2HFuGuoku6hrNkqW34cxIBf/2TwLk759uliaFBlnBmR9EW5fIYQ6cSTiJ6JxE9mYiOEdGXEdFFAM8EcAuAZxHRhaPYyXWDCw1qrMcbg8FgMBqD8nHzzagu0k6+xLopnCus4fTvt6JjMsjUpVHWkg8xoAQAoNSGEc6AZLZtqRWWmFcVznMHKa6UVuHcZMK5djWcjg21FBrU9Ll+eBZ4688BH/uLuV7mTtvRtihHFxp0SYxjNTB3DSYRnSeiPyCiU23s0CYgy1nhZDAYjHVF421RsKaW2oBw6iMmK6uu4fzyn38zfvNt86kZ6wihhuijCwDQm2ZP1mENZ7v7LqwiFvbhVJpwcZDhuDgEAMTZ5hJON59cuxrORhXOfPz/m9x2aFGv8zKXUqsqNZy6qO1sixBySi1jJlJui8JgMBhri6ZXjosazvUa8wVpaBIAAHXUIRwrJpz37fZx6sJg9hPXHFKlOHSEU20a4QxqOFXLCmeQUusI54V+BiLgGAzhjDaZcK5tW5QWajhl3Lyl1hHOOcdBN6QPs/FtUYD2bLXa31bW677SFphwzgkiQqaaTUBkMBgMRnNwhLMphVO6Gs41mxgIEDLEAACdH+1EdZUKJxFBabokyloiPUSfNlPhDFNqqeXzQOjRPpznD81jW/oAwIYrnIGldi3GmTYIpyOZyXbzllpPOOdTOF1dflXhDAlnW0m1rHAypiILSOblUujLYDAYm4SihrMhwrnGNZwZIgCAPuoaTlod4XT34Uuh9imiDH10ABy9LXpphApn24RTFZZaV2+3awlnN98HACQbTDjddDJThEG2DuNMGzWcdlvJVguWWnsuzm2pNT+rNZzhYtZIUu1DtwK//DnA4bm5dzPE09J34LWdl2zcQtOiYMI5J8JVkEvhZsdgMBiXGnwNZwMuFK0JUrhxf73GfAFC7gjnESucq7TU5lqXfm4yYp0WNZwbZqkt9+E8mhrObpBSe/4gg4RGolwN536r+9AmwgTstQgOajOlNu41b6l1Vlprva69SxNSakNBaSQ46PStwJmPARfvm38/AzxW3YGnyo+Bmj4WawomnHMiy5lwMhgMxjpDN5hSm2vyllqsGcGR0IWl9qhDg2h1bVEupbKWDlIMyCqcG6Z0iFJKbbv7LlVhqXXk4Pxh6us3ASDJN1fhDKeTaxEc5OvWW6jhTLbnrrWcCW+pnY9w0iSFU00hnA31ZfbXz5rdV9oCE845UVI42VLLYKwEpy4M8N//4lZOimaMRZM1nJoIke93uX4Tg3RFNZxilQqnC+7b9Otf5Yig0UcPwOYRzrAPZ9uTZkHWUovQUpvhhOj75yQbrHCGitp6KZxt1HBuNbtdIEipnZdwFmm0IdQ0S21jhNN2vNgwZ8OiYMI5J8JVkEthdZXB2ET83Ucfwq/e/HHcf6E/+8mMyw6qwZRao3Da7bS5yHh4DujvzvUSSRo5uRrOI560NDTpmorhHnBwZuRhr3BuPOE09WYqtoQz36wazrAPJ7VMOJ3C2REKWWaIy/nDFFdIcw/Ypx46+eYSznBoWYuk2jYstaUazqYVTnsuzhka5IaQEcJZstRWjoH7W0OEs+3653UBE845kQUKJ4cGMRirgbsO+RJkjINTvpsgJCq01LZ5wv3xdwOv/765XhKm1NKl2Ifzr14M/N7zRx7OLhGFMx2ati463gIQHNNNQbC/uuVJswwIisrMcTt/mOGGriGi99E16KjNJZyhW2c9FM4WQoNChXNNLLW+D+eIwln8PtIWpaFygnUt1WgLTDjnBIcGMRirR5pfGhNORjtwp0UT54fWhaVWNFnPVMH9996FT9x771yvCWs41ZFbau0Er02isXs3cHB65OHcLyhs9kRt/8AQJEq2AQBqwwinOMK2KCHhpNSomhf7GR7WMeTzfroanfxgYyfv4VC1XoSzjRrOLUPamlzAW9hSa36OWmqL/7dVw+lev3ELTQuCCeecyPLiAuHJLoOxGrgJJ7sMGOOgqDlCElpq2zzbsnSAg8F8kyUAPqX2qBXOIkykxQl+f3dsv75LpYbz8NAE3ghLOLFhtVwlS23L+y51cW1oq3DuDXNcHRsL5f24xihG6WaqnGFK7cX+GlirW0mptduyin4r257bUjtb4WyLcEq21DKmgRVOBmP1cGnRTDgZ40AN1nBqCi217U0MYkoh5qS0EhqZsKFBR92HUx9Bb9L++bEWuUulhvPw4AAAIDubqXCG10PrNZyBwqkzW7c5yHBVbMjnKVxj/ji82Op+tAV3Ku90ojVROFsIDQoVTqAdwrmwwln+nKHCORix1DYUGgSz3U0LC1sUTDjnRLgKwim1DMZqUNRwrXhHGGsJRzSbCHbLS5ba9k64DmWQc1p2BQhqRTWcTdUxTUN+eB7ZmAmkU643fdH3sG/7R3YN4dw4a11AMlu31FJAwpzCOchx0oYGPYirzd8Gm0k44/wA3xj9Ha7oxevVFqWVGk6n6Df4OX1oUDM1nHlJ4ayGBjWVUkv254Zd9wuCCeecyFjhZDBWjowttYwpaLqGs1Ae2zvfYmQLKJwEJVbTh9NPktoiGlpDDi8iS8cpnOY9Nz0pvm8JZ7J1DMAGEs7QUtsy4YwCSy1yQzj3hzmuEH0g6mJXXGH+tqEK56PPvRUvTX4dn9J9cM0UziZTah3h7DW/7YUtteZnWlm9Du8drfXhBLdFYUxBSeFkwslgrAQZhwYxpqDplNroCCy1CWULbL8gnNR06uPMt275mKR7kNCIaXRS6iy1m379DwZlwrlx1rpQ4Wx532VITqyldm+Q47g4BHoncCB3zN82VOF0IVzXdrL1aIviW0E12YfTtUXZLv/e5LYX7cOZLdCHc8lz3jla6DJZOGfCOSe4LQqDsXpwWxTGNOiG+3AehaU2WVDhzEVifjniGk5hJ1uirdCg/nkAQEfkyCv1Vbmv4dxsT306MMSp5xTOTVM6jrCGM6IMuZ2yCjWA1oT9YY4dHALdEzgUlnBuqMLpjuVVSb4WCucws+NJmzWcjVpql2yLMkHh7MRyjMLZUB9OcEotYwrCk3LT7TwMxqbCWWq5jpoxDm5oboKQaCII0XJKLRG6WKSGUweW2iOetLRtqe3v+v9e7Jdtcpn9Xjc9NGhoCWd321lq1yCddB4csaV2H0YZE/kQ+7aubkcfAL0TOJTmGGJwodX9aAtuMevKJF8LhTN340lbfTjD3xvZ9mI1nG4EGUmptXOL4914iqV2yT6cbbtE1gxMOOdEeFKywslgrAacUrsmODgD/J9vXrtJnrPUNqFwqqNQOO1K/7wKpwBBryil1h0L0dI1ONg76/9/8eCw9DevcG74om82NJ8r6rjQoA2beB5lSi1lOPCEc4D9gTnft/QB0Lvi6BXOBz8M/N/vHtu2ZyHYY3kyTnFxMMc2//xHgTve1Mw+BPDX9bhx5Y0/DHzirfNvVFUttS3YdfM5azjtPcKn1B6eA37/Begd3AcAON6L0c8qx0A3s9jGCidjKrLgBrfpq6sMxqbCWWo1X4Orxf3vAz7yeuChj6x6T0rQvg/nphDO4ULbN6FB1lK7spTado7J3m5BOC/sVwlnMzXcFwcZPvUn/hJvu/3MUttZFPnQhN+gY8jSxk08j7CGM9I5DsS2/f8Ae5aUddU+0D0BJbtQiI6uhvMTbwU++L+Bw7Ozn1sDro7vRJxif5j7c3wm3vUq4La/amQfQvhWUNXvlQh45yuB2/96/o06RTPump+tWGrnI5yOV3sx6dQHgY++EZ/68V8HABzvJe2FBvk+nJfHPIYJ55xIg1qSTQ8sYDA2FUVK7Yp35HKHu8mvmSVINaxwuslXaxMDG3Qxt8JJBeE8ajtmEeXfznd/eOG0///+YZlwutKWZS3TFw4z7A9z3HPucPaTW0Buw29EZ0PbogSWWt3yGBBTigOrYop8iP2hISudfB/onYCMJPrRsaNTOD3paOg7s9s5Ic3n2qurcpIGsubPXz8WVccVRxIXGW9UBsgYkK7uvA3COd823eLk0BFOe00+7v7X4zqcx7FuPDk0aMlzfiKpv0TBhHNOhAon2/kYjNWAU2rXBGtKON3Q3FQfTjcxmJcQ1oZTOOckbxIaJGO7jaMlnK7etC1L7TCw1O4dDkp/yxtKqfXhUiu6l6vUfC6RbCrhDM7X1kODck84Iz30hCzO9oDuFYikwEDuHJ3C2VBSqYO7jnakGQtqBweR9n1Jm4UjnJXP52okFxlvdGbIZtRC0NmiltqqwmkJZ0QZvjN+I473ptVwLkk4ncK5adf9gmDCOSc4NIjBWD2KlFq+BlcKd6NcsxumajClVtMRtEWxfQXlnNsXQNEW5agDZ1oOvMgOzvv/Hxz2S3/LGwoNci9flTVfZXahwSqcepNrONsODaIMh95SawhnBIUoN21RIinQlzsbq3C647cjDKG7OKhBOIkAEJD3Zz51Xnh7/4jCmY5/vA5UbsimbKEMwNdVqrnuR4SKwmnH4gdOPAXfFP01rksOW+/DebnMY5hwzgkODWIwVo9PPnwv3tv9LiDd0Aj8SwVrqnAWNZzL75ex1Lqxvp0xn3KncM6xfSJIQSC5WkttW3Wt+rAgnPsVhTNThL/o/Ai+Jvvz5d6jwYWJRUBWmXKEc90WbmYiTKltmSzHlGEgelCIEKsh9oc5jsESre4JRELgUO4cWYDZ3sAQr6bUKXcdbcGcE7UUTnftLatw9neBn3k0cNfb/UNyoqV2CcKpnaU2Kn5vCuH+zJFU6y79qqX2lkd+F3bEEJ9/8Dfop5XP2pil1qafN9nrdI3BhHNOhH0469Z0MxiMZnF1eh+uEvuIBrur3pXLGw2l9TUNp1g1FRokWw4N0tkCllpLlnQbakENFMeinWMigrYoh/2Kwqk0Pkncj4frB5Z6D/KW2qU2s/j750NoSMikZ/dns9qihNdD66FBlEGJBEp2ENMQe4MMx4WtXXQKp9g+Mkvtx04ZYru735C66AmnGQsu9mucC55wLlnDeXjW9L09/wn/kBuL9CRL7SJkUWVG4WzBUqvC2s05bLVuDPD5LJZw3r/zZOQkcSXt4jBTZRWygT6cOgyj27SFpgXBhHNOlAnnek2yGIzLBnZyvXGN0i81eIVzvdwejmc2UfZQSqltSeHMndI1l8JpJ4SuhnNlCmc7xyROC6XqcFCt4dRIhIJckqCt2lKbUIpcdhBJMxXbuFquYH/bt9TmUCJGLruIdYr9QY4TjnB2DeE8EEdoqbXzP9VYWxRzDibaEJ6D4RyEM19S4RxDoNxYpKshPD40aIFzVefGTusXyZpTOAfDQNVcQOH05XLWnjxEB0Mk6CEDUaCAAo0onJrCMLrLg0sw4ZwToaWWA0sYjBXBTnb1UbeCYJThCed6TZQbTak9gomBUzjlXMfRfDYpJHKSR26pdfWmbam+SXYRGgIAcNivEE6b6jvf8RqFP09WtGASUQolEsSRhCLRevBO8whVn3b3PaEMueggl10kNMTFQY7rO5ZYWIXz8AhDg5zipRtb9DTHL7KEp1bJli6rcgtjTACSs3uqvDKuOPVw0ZTaKDa22kW3MQGlucACCucw1+b/2QAQEilFGKKDrq2pLSXV+pZQi48bmsCEkzEdqSJ0YnPYODOIwVgRnMK5ZkTnssO8NZz3vqfZ3msT0GgNpypqONtS83RqCecCCieENP0Hj1gdE2i3LcqW2sNBdAIAMKgonGQJZ7S0wrnaGs6EMuSyCykFFOTGKZyCjkjh1AoSGkrEUFEXPaTYPUxxbWzPC6tw7juF8yiIu3MYNKZw2gUca4+tdUp6S21DhNP/DLoxjCicLqV2EUttalNq2yCcwf7MqXBKYT5yrskcy2QbGsAAHfRgtnWYhYSzGYXTh9Ft3ELTYmDCOSfSXGMrMQXPi1pqn/MLb8YfvvuepfaDiPCqt9xRPzqbwbiUoJ2llhXOlWKeGs69B4FXPRu49c/a3Sc0SyQUEWLhPl87xETli1tqhYyQ4+gVTjFmctokjuk99JOrAACDYXlCrV3f0iUXnNyur85Sm0HJBLEU0JAbGBoU1HC2GWphCYSSCbTsoosMZw9SXJNYJat3BSIhcIBtAASk++3tiwV5wtlUH067qOUJZ41zsjFLbZVwBuGY1XvsUqFBLqXWtXJqbv5amgvUJJxO3XRz+mGujaU27iFXhBQddMgpnMH2G7bUrptDqC0w4ZwTmQoJ5/yvz5XGraf28PHTB0vtx51nDvBTb/gI/u7Wh5baDoOxiRC0nlbOyw7zKJzZAQAChu1PBlWToUHBhHIdQ4OMOhYdeQ2nt9S2oHAOhilOiEOkXUc4yxY53bTCuSJLbYdSKNmFFIZwbpxjI1h0b1XhtBbJXCTQVuE8s5/iKqdw9q6AlAIHtm3KkdRxOsLZ1HVntydzQzhrtcpoTeGsQzgXOFeVS6ltPjSIFggNcreHnp3Tp7ntaZpsQRNhKDpILOEstUZphHAGKbWscDLGIVMaW53FFc6BrQHNl1wNdAXOGUflMi5HaFfDuWETtEsN8xDOBpL96sK9VSN9OEPC2ZLCqe0EKZqDvDlyIkQEtQJ1zFlq2yDhZ8+eBgDo7WsBAMMK4XSTywiq3sR8AnSD58m8ICIkyEzqqrXUbpq1rrTY0CZZtt+3Fgl03ENPpDh3MMSVUdEWJZYC+9gxvx9FHac975ty2bjraCFLbWMK5+gYras1nMuk1GqXUttyDWdN5dQtOJUIZ94Hki3kWiNFm4STEInlt7NJYMI5J9Jc+5NzEa7nCo+XXXl36YvcC5RxWcLdqI662T2jDP891JhsNtS7rA4UNadwlurqWhpvKTUT53kIrdbOUiuRQ0IcucLZXkrt7jlDOMXx6wAYgjkIaqhcDWcMtRRZXGUNp9KELjJo2YGUAhpi42o4ywpni8cwsNRS1EMXGc4dpDghjP0RcQeRFNjD5iucjnDWOifDtijLHP9pCmeVWOZLWGpVZlNq27bU1lM43SHrJoYKDXNl1OK4B6WBVHSQaLOtftOEU7OlljEDqdLo+tCg+S9wd9Nc9gaXN2gZYzSMBz4IvO93V70XlzTcZPeo69YYZdA8NZxHSDgbreEsrfC3ZKnNXUrtHApnQDhXERpU7Gvzx2R/1xDOxBLOBAoXg7wCnZv/x9BL3QNphZbaXBO6IoOSXa9wzlWTOtwH/u6njySEazKOqA+nJRBKJKC4iy5SZIoM4eyaYKlIChxgyzy/DYXzQ68F7n138bsnnGtQw0l6ufNgGuGcqHAu2BYlStqx1Ibbqm2ptQpnHFpqjcKprMIZWcJZVjgb6MMZWGo3zdmwKJhwzolMaXQiiUiKxSy1mVM4lzvBnCV3VWEHjCl4728Df/ljq96LSxq+hvMyGajXFfefN/WY956vUZM+DzldEu60WLZ0AQA0hTWcLSmcmQ3BmUvhNM+NpESOaDGL2xJwq/NtHJPDC2cBAL0rbwAAJMix2x9NoYyRL6lw2p8rUjg7yECRUefmruH8xFuBN70UOPWh9nZyBsQRqP8ACkutTEDxFrowv19Be8DWlQCASAicEteY55+9vfl9+OuXAO96dfG7/bzN9YIO1ErUPJzhWJovUcdZJVDBm48s6i4TGuRqOKOWCWft0CDz05XJmdCggQkN0oRUhISz+dCgiNuiMKYhzTU6sSOc87++7wjnkj1VMsUK59pC5ytedb704SY6ja0uMxbC0DbbTrM5mpQfgZrUpMJJR1DDScrUYMmFajglFM2pjjWAon6v+WMy2DOEc+eqhwEw1tkwkV37Gs7lFE5HNFcRhZArY6lVsusJ51wLaPO2JGoB4qgUziA0SMRd9GxvxBPqHHDMqOBSCpzGVcDJRwJ3/33z+6DS8rF2NZwNfW5fw6lzJMjnUziB5YKD/Ng8uig4QqiXaYviajhltPg2JmCRlNqihtNZarUh/Mk2tCZkogNp1fV+021RSpZaJpyMMcgUIYkEIiEWqp8cZDY0aGlLrdnOqvqHMaZA51xb2CKIyN8YxRGrOowK7PGvNek6yhrOllJq29p3p3DO04ezsNRGVuE8aktte6FB2cE5AEBywhJOoXDhsLjWhZ1QJkvXcLqfq7DUanSQG4VT2NCgeY6le+4qF93GELBWYIkJyQ6QbPneiMeys8Bxe45IOyd75DOAu29pfmFL56VaO3feN9aHMyDvWxjUCw0Kv/tGCOfoGE3Ve+xSCmduazibVzhL28rnJJxxNaXWKZxdSLsYWLLUNuDWKVlquYaTMQ6hwrmISukVzoZCg8Kb7Z1nDvAP911YaruMBkD6yO1tlxOUJsRwNZyXx8rgusIluNb6Hja0hpOC1hvtKZy2hnMuhdO1RZGm/u+oQ4OcpbaFY0KH581/doxFslOx1LpJcCTUUuUp1OB5Mi9MaFAKHRWhQXORxyO8niYhVNVbtQVakqNlApH0rKWWsJ2eBY5dD8AonLkm4JGfBxw8BJy7o+F9yMcrnE2l1Abn4DaG8yucyyTVztUWJXN/mP99dGYSar2ltsF5ksoxJBdGVDM0yP7s+T6cylpqTVuUXHQg8jGEs2FLbb3Vhc0HE845kSmNxNZwLrIq6pKuFqn/rO4HUCauL/vLj+LH/nh19RwMgzSz1hsmQ60gU4TIEs6Na5R+qcEpnGsXGmR+5pqWTs9UeTjJbGlikLs+nPMonObcly406IhXyYsazua/T9HfRYoO0DkOYNRS6ya9TSmcqwoN6ogcFHXNvkDO9x1WbZArQOm7b/N+p5yltgOR9NBDimPoI1Z9b6mNpTAW6Uc+3bymaVutnkA457gH5Urj2T97M/7yH0+NewP/v20xnK8PJ9CwwhnWcFY+nwvkWYQsqgyIOkFKbbM1nAN07HZr1nDaj+tSasPQoFwRUtmByIfoJRL9Fmo4OaWWMRVpKTRo/pvUMDcnVrZkDacjmmHYQT9TGGZMclaN209ZlZlVzlaQKo3YF9tfHgP1uqJIqa1jqT26Ppzh2Lz04nFJ4Wxp3/PCUls3wMaRfOnaohw14XQ1Zy0ckyi9gMPouFdCEpHjwmEwiQz6cC6Th+AWjVcVGpQg959RL2qpXanCqZGTmUa2q3Daha0ohky2EAnCDcLYrp3CGQmrcF77BGDrqhYIZ7Y04dwb5Pj46QN8/PT+6B+DbW9hOF8fTqAhwjlmjB5ROJew1GpnqY0AiMYttYfomf/Pa6l1fThVQTg1ETLRBbI+tpOohRrO0FJ7eczbmXDOCWeplW5wmxOFwrlsaNCowplrWslKLaOM3MWIc3BQK8iVRiTs4N/gCiljfpCbCNZJahwTSNEWQvfJsonguhQa1NK+WwUngq49hutSW5TlLLWDTOHsfj0bmkObltpttY9BfMKTsZ2YSgqnaEzhXJ2lNnelAbIgnHOpxWtSw6lgJutHYaklmUB2TOuTm4RpnROGBmlNgBDGVnvX+imcB1YlG3eJh9/9YpbaBhXO8JpuOqU2supmlDS7KK9zHFLXvs98bVG2nKU2VeY42pRaJTsACCcSasVSy6FBjKlwllpv35gTbdZwKq1XEn7AKMP3iGTC2QoyRaxwrgvsZGse+5c6ggmyLo2Ly42JOiSsLQ2vrk5ICiq/3xSQ/VxSCChESymcv/7mO/A1v/y2uV7TpqX2OPbQj457MnY8oXINZ6hwLtWH0/xcxUKt0toQTjsBJ7GopXa1CmdmCWerllpr41SyA5kYwvkI8ZD527EiNMh/j498OnDu48D+Q828v9bmOJfOExsaNAfxcqRl3NwxXLjZFosonO3UcE5si7LIYq/OisAgGTe7KK9z9GEJZ02Fs6jhNFQoz205VLIFpQmZNNu7oqO8WGRe2EQfzqCGkwknYxwyRUVblGVSapfMYfcpteFKvqKj6DjAmAE38ctzJpxtIFOaazjXBb41w+zv4fyBmRDddqqFpuwVaDKN4IHlF/fCUJD2FM5iglTfUmuPuYgM4VxC4Xxob4gHLvTnqnd112AbCudxOsAgPu7bJxyrKJzSKiMxlgsNWqWl1i2cCVvPZtqibBbhBLRJ17X/bw1BSm3U3QYAPNITziI0yC8u+TrOW5p5/3EtaPxqRf3r7mBonjt27hhse2flNZxhbW6TCmdhIYdMmr1/6xypuaLmb4tiU2rVwFqdLeHMLeE8meTthgYx4WSMQ5oXoUGLrJw3pXBmYxROTcQK5xrArfin6XwWNUY9ZEENJxPO1cLZyajGeDawdrIsb/87U2TaVwGAWrJenkqtENoZX0WJcNY7PkVbFNNSYxmFM801NNk+dDUReUttGwrnAYbRcWOPjDqjltqQcC5Vw2l+rqKftUnbzpe31K44pTaDtUi2GhpkLbVRgrhj6vRuEmdAMga2rgRgFU73Pd7w6ea43veeZt7fWT+DY+2+q3kstV7hHHe6hZZacdSWWtcfaEzZw0ho0DI1nFkRGCSjRi21QptzMUNSP6XWfmxXw6kcabeW2lwYwrklsvJ8vxHCCQjBbVEYE0BENjRILEw4B45wLqlwuvcO9yHXxH051wDChoykQyacbaCUUktcw7lKOFWtzqRLzxMwtCSICJ3I2qQatNS21RYlXJFXNRWTEYVziePqMgFKq/gzUFhqmz8mERS0LJSQrZjKfTgd4RTN1HCupA+nUogEQUSBwrlhNZyCyCuc7dZwmnuplh3ETuGUDwE71wHSvH8pVyPuAMn2cq1CQoxVOOdPGHUK5yxL7U5dS22pD2c7ltqR88srnIum1NrrOkoat9QqkshEskBokD2HU0s4ky1oTchtgnRvIuFcbuxhhZMxEU5VNKFBi9UGOcLZVGhQuYaTLbXrAK9wZvUGPcZ8MAqntfNx65mVYp6UWqfItToxtVDalD64/y+Do7DUymBFnmouRvpJqwC0WM5SO/SEs+Y2iHzCYhvHRJI2NY0AEMXYjnS5LYpXOPXUBYW33nam/LoKVtmHU7tJcVDDOdeiQQPN55dFSeE8ipRamSDuGMJ5kzgDYQODAGOhLxE5IZrbJzXZUlsrMM2iUDjHEE7S/lhuY1jP5t1WaNBUS+2CfTiJKjWczVpqBSnkiJAjnsNSa352YgkhAB0QThMaZNT0HtLyd9ZAAJ7W4D6cjMlwJM+EBsnFLLVpQ6FB9vVh/Uqu2FK7DnATsCxlwtkGQsI5j52J0Tw8yakx7hQKZ7tjFBFBEwKFc7lJZ3iOtRGQA5QttbVDldy+iAhKRD6sbBGk+ZwKZ3hMWlB9JTTgCKdMsCU1dvuZJ4iRPe9i5BPvw4NM4Vt/4x147Xvunfg+vg/nCjibsmnmTuGkhS21qxwDCcq2RTkSS61MIK2l9gQOgOMP80+Jq7kaMmqOcE5ROOta4IEipXa8pZbQF4ZM7yxiqW2pD+fIIohbHJt3gcsdJ1/D2aylFjpHjgjpXJZau2gmhLlfeEutqeFUlhx3kFUIZzM1nMK7RC6PeQwTzjkQEk65aGhQrvF0+Y84lp1bal9yr3AWjynNhHMdIK3NM8vW3FJLBPzj6zautUiYUnu51D6sLcjF/NdROI9GkaFg1RpoOKW2JUhdEM66CrB/nhDQR22ppXZJuAT5wCBEHfQiDaUJB6lzNoQK5/j3z5SrS538mTQRvlS+B7FaYrK+ILQNlRPSNKvXYvP6cEqrKgEtOxesGqzjLhBvFY8HCqesljlVj+fBGeD2v1ns/cfVcHp1ao6U2uFkhRPQ0CICoi62RVozpTZ4Ult9OCdZamfZYT/2V8DgQrAd+3wZtEVp0FIrSEEhMipx3ZRa+3GlEOjGEuSOYdKzoUHmXNvCHDWcZz9eqyVPyVLbZuDWGoEJ5xxwq8AmpXZBS+0ww28lP4OvGv7ZUvtShAYVJ6oiWslKLaMMNwFbe4Xz1IeAP/wXwJ1vWvWezIUs6MO5jI2QsTzEHCTSWWrbrjlzC4FJQzWcpdCgliYGIiCcOq9Zw6nd6nxkLLWNKJw1r6cjUDhDS23HXu+uBk5S0RZl0n3Yn25Tvv/O4YN4Vedn8ZkHb2loz+tD2cm2r+Gc9zusBr3Mib1Bht3DJe9RgQ20XUut2U8hYiDuFo/bhFoAiMQMwvm+3wFe88+B/u787+/uM+GxXqCG1iuc42o4iUzCamcb22JQU+EM3nuZetWpCucESy2pyW6V4R7we88H3v97o68rpdQ2d/8WOkcOiRTx3H04pQA6cQRyxzDZNgJOZBaDutUFgEmEkwj4g38BvO57arw3uIaTMRmpZXOdSCJa0FKLdB9dkaOrl1tR9W1RKgrnPLH2jHZQtEVZc8Jpe5v5nxuC0FJ7uQzU6wo/GakVGrR80EIduElEczWc7afUytBSW5N0FKFBJnBmGUutUzj7Cyicso0azoqlNoE5z1wGgnORxFP6cLqFh2lfv7AT01gf/RhIVuGUbgIOcaQptT/5+g/je17z3oVe6yBIH43CqVIMkSCKJJCECmdAOKWApsImCVFpM5MPARBw9vYF3n+0dEAsQDidg2CcO05AgyCBZAdbGNYbJkuW2sPa+zFxO2POKTGSUhtcK5M+u8oAEHBwOniuPYZhH84mCadVOI2ltp5y6sYGp3CKIKVWEUFHxr7doWoN5xglGDAK+oMfqqU2K03FYt1lMo9hwjkHSgqnWCzZLkpND7oOLXeDy8conLnWbKldA0g7eOTpmvfh9IXvm2VLNSm1bKldB7jJSJ3JJjUQtFAHbkj0CueSbVHKk6J2xtcotNTWtPA6Am8UzriRGs6DmoQzbAbfNAknZzUTzlKbILELTK5tS9iHc1LbmzoJtPOEXjUN16e5pHBiHoVzuevp/EGKswfLzUMENHI7jWyrvhkAoFJkFEMIAHGveLwSGgQEC0xClhe33Hd95mPzv/+UPpx1ygkcnEI/9pQkDRJW4cQiNZztpNSO1nAGC+mTCKM71qGa7BXOuPjZKOG0CifFtRfR3TEWAoZw5kVokNIE5VJqkdaz1L7158zPGqFFfpwbt51LFEw454Czsbo+nItMZGS6Z7ZBy6lfbl/C1V2l6HIJu1prSDtpyNe+hnMzB7uSwsmW2tXCK5w1CKc6mpTaxhXOYH/bUPOAcg2nrlsX4VJ/hZifrFSQ2vtJv6alVgV1kU3bjDVVFM4o8dd7VeGMBCGfkBLqbIvTvv6jsnmPfW9nqY2N4kNVgjRzA8vtuyZaejHGKJw29Kjl0KAMMSIhKoSzCA3yhNMrnJXQIPf/hQjnaA2nq7tbrA/n+LYoRuHcxtYihLOFlNqMojGW2pBwTlhUd9sZ7I4+N0ypbbCGU2qncNZPqfWnihAmqdZZauOetdQawtlBDUvt3e8A7nob0Lui1ucKLbWtLtasEZhwzoEiNMj24VxgZTfOmiGczlIbDkq5pnpR2oxW4QaPtbfUrkEft0WQKV0M1Bu275ca5Bwqiz6i0CA3LnciiRg5HvbWHwMuTE4qnQVnqdWQrVlqI51iSJZ41FxEKRIWJTSWS6n95MGH8L3RH9cODXLqHNB8DafSBAkN4UKDZILIW2rNuRMFx0hPmNx5S+2Ue6I7J1cx4XP7LUsptfMonMstGGoCsiVJooD2fTjbruFMERtSmdRVOMV4wnm6GYXTnzMLKJzjFsEEaRAE0NmxhLPOfjXVh9NZO932rKCBaPTaqKNwuteMVTjbs9TmFGFI8xDOsIZTIlLVGs7AUjurD+fbfhHYuhJ4yjfUen+21DKmYlgKDRILkbtOvm9+Lmmp9QpnsEKpiVNq1wFu4pevex/ONejjtghMSu1m7vulhrlCg47IUus234klHiNO4dpbXwPc+ebFt2f3W4kI7VlqMwxgJmKqbl8/u19CSNCSbVG+MHsb/m38utqEMyTFTau+Lr2RAkttROUaTkdAgaCfZQXKK5yTvzOxwrICbesCpQ0mISF9OUYtLNkWRRNNtCPXhQxqOFtN2swN4ZSyqnAGhFOMs9Q2pHCO6cPpF5/mSan1Cufo34QLykq2sS2G9fI4/P6IhtuiWIUTY6z64QLPpAVfTzjPB8+t1HA2bKmVpKAgDeGsbam1r7U1nNKHBvVMiZolnF2kZYFp3H3vwX8APunZQO+kIZwzvr+ypfbymLcz4ZwDWRAaJIVYKP3QEc7usgqnmqBwXh7n7VrDWWrVuhPOjVY4N7P+9FKDmIdE6sqkpiUUKbUCx2AnYUuc484qqBG1ksgKIsSUoo9u6f1mQRezJeglCafUGboiw2BQTyVxNtYhxY2rvkoTIkGl0CBHOIe5aY8SBzY/NSHV1/OBGpbaVTglqKpwCjmXPZmWvJ40EbJlJwykoXxKbYuTD1vDKQVMuxyZAJ3jQGfHP8UpnP7yEbJ8f3D/P3/n/FbOcTWcvi1K/eM/K6WWbErtFg1Kmx3manyCtF9dO7akpbYyjnvCOcZSG5K5ScfRbS+01FZrOGXceFuUHPMpnLqicEoXHhZvQWmAYmeprdGHk8iot1EHAM2852gCYuEstZfHPIYJ5xzwhDOWiKVYSE3sKkM4EyxHRtwq3mgNJzPOVcNN/CZNhNYGG1rDmSvt+3ByW5TVwp3rdeqY9FERTu1qOCMcE3YStswNXRcKZyttUeyka0C2H2Pd4+MVTtMWJVqihtO1GckG+zXf2lx3eQsk3Ntc5XiFM1MaiSg+K02y1NZQOIv63KMfAz3hjJ3COca+OAX3nzff1dm9xYiG1sXC9aKQ0Fb5R7uLfyrF0NVwAiapNlA3gYJw+r6sIwpnoEieu2O+9x/Xh3ORlNoZfTiNwrmDXqWG87+94SP4tt941+hLfNPhnYZCg2wQkp6mcC5oqR1XwzmpBnQBSMqhbFsUmjM0CBDoxpGx1EZdQEoorSFlBEQddGg4wVIbnl/K1A07y/AM0hv2d26rVGPdwIRzDrgkv0VDg4gIW7oZhdOtTIa1AEbhvDxO3HWGs5ipta/hrNZtbAZSRUUfzg0jy5caCoVz9rhzZJbaoIZzB3YStszChN1vLZpX8wD4nnF9WMJZ01Lrxnqy+7aMwhnZiZ+uSThVQDgbt9S6QKIJltpcE+LQUqvGf7d1ajgLhXOFNZzxYgpn36ag9xdMQ9dES/eoFURQri1Ki8eQchMaJC2pRNwFjj+s9JyR0CA5ITQImN9WO66Gc4GkdK9wjrPUhgonBqXnPLQ3xL3nx7Q9ce/d2W40NMiRobHXt8oK0jiLcA52CwXYXaeWkGkZ4/5z++M/1wKQMAqnaYsyX2iQFOZ+keiBrxFWmsw5FW+hSxVL7bjFBtKmbtha5GcTzvDYXR7zGCacc6AIDbI1nHNOPoa5xnGYi6uDbKmemW5lMiScii21awFHgibVFq0N3M1qAy218QI3e0bzcGmhdb4HOqI+nD40KBaFwrnEZNhNvkwSbAv7bseJoSWcdVMv3TgjZLR0Daf7HvWwHuF0pDhD3EJokP0cjlzIBMIS4kGukSvt+3IChoyMg7u/Tr0nOpV4FTWcebmGE/P2UtVOjVphSi2UVzjbVGnIptRKp3B2jk0mnNNqON2xnptwjllY84ppjeN/7g7g5z4FVwxPmZdM7cO5PaJwaiIcZmPex1tqdxqt4XSLgymNUziHQLJtd2wS4QzCcGxnBk/ApFlgOciAg/4Af//xs4vvdwDp+nBSPHFMmLSb0qbUxnoIxKbPq9KEWAog7iKhtHwLGdeHUyuzyOEVzukLQeF1y5ZaxgiqoUHzxu0PMuUJZ68aszwnxrZF4dCgtYCztqm8ObtIK9hgS607xqxwrhZyjvAmrya1vJrrhsROJIsaziVu6G4y0GQN56kLA3zFL77FrO5bhXPgFM45+3BCSJCUxXcxJ4jIK4iU1iWc7SmcTj0VgcLpCPEwU0iV9n05gapSEGzHiRBT+3CuroaKRhTO+Sy1TaTULtsySBBBC7v/bY7F+RApJZ5U4mt/BXjmfyw9ZXxoUEWV6uwAx28Eztw28a3GCgFqSUvtmduAi/fhUdnHzUvGEU6yltrODrrISsFcSmN8oJfbh6RZwqlCS211XFGZUVSB2QonUNhqnX3WEjIlYsTIfRDYsohImT6ciP2YOgu+hlOaPpyxHnqFM3cKZ9IzKbUzazi1OedqKpykKq+9DMCEcw44kudCg+YnnBrH7Yp7T6RFrcEC8G1R3ConEZQmEE0YMBlHBpc0SDVtHSvDkimHq0IapNRyDedqMU9bFG+pbdm+qH0NZzOWWvI1nM2pee+9+zw+8sBF3Pbgvg/hcDWcdRUrN8EXQoIQmcTDBcb+XJNXDGl4UOs1Lkm3jRpO//mDGk53nQ9zjVxRWeFcpobTE87Fzsk3fugBvPDXb1note6cjCLXh3O+GmF3PVHdVOPq2xMt3RZFQvnQoFYX/1SKDFGhcD7684FrHl96ymhokCiRwTtPX8RuX4Gu+WTg9EfHvs0r3/xxfNnPv3m0tnVsaJA5r2otVtj005PapLaObYsCa6m16mGiippMIkJqA7NKCBXOvIkaznIQUoYY0bgazlkKZziGueAgVa7hzBEhhvatjpYCESK4PpwJxJyhQa4PZ0cP/GfTVFhqExrWIJyuhrOmpTYIY2rFObOGYMI5B6qhQfP24ewHCmcX2VJ2lryicIYDEdtqVwu34j+pP9zaoHJz2RSU+nBeJiuD64q5CKc/z9pWOAvCeVw0mFLbYGjQXWfNfWCYa084+3MqnJ4sCQFtbWqLfM4ssKiKrB7hLBTOFiy1qkI4raVWCFvDGbZFQhFgNLKPNJtwuvNWLKgOf/DeC/j7OxazBBYKp7XgLdgWZVFlUZNZn1hG5TQKp1xqP+qAVIYhEkRTZqyzQoP2+ikyAvKrHmcUxzHnxTvvPIfbH9rHW247U/6DDw0KbZBzLNjaa/xa7JqXjK3hdAqnITyxLhRLdw6PJNVWCeei9/KKPTis4SyFkRGZz+II58SU2lDhPG+37Wo4O37bsVDoN6Fwut7n5BTOmpZa+1PA3C86lPq2O17htJba0hrEuD6cXuGsZ6kdqf+8DMCEcw4UoUECclFLrSgstcsU7GeVGs68RDiZca4SzoIyaSK0NtjQPpwmpZbboqwD5rE2L9vGoS7cmJhEEjsNWGqL0KCosTq1u8+Z+0Cq9IillmqqsX6Cb/twmp2cf8xJc42OsGpbXcLpVN82QoO0s9Ta6UkUQ6gMvTgyKbW62F9gssJZEM5pb7acNT9TemFXkbs/RCHhnOdYLtnWSvu5w+Lfn4D2ltpWF//yYbmGcwxcoJCf/4jR0CANicEVn2TqCvdOjWzjjjPm/H/tu+8pq6Bj7pVzhQZZ9fFasVvexwBm4UYYeyyAjioIZ1ft41qcR79qq3X75drDLKpyVms4tavRrjgntAJAgaV2Rh9OoLDUVtqi5BQhRt4M4bRjhkKEjGLjiKhxXrvr1vThjJDQEEi2oK1b0Fhqt0xK7SyFU2tbw1nTUhscu7kWmjYYTDjngA8NiiWiBSy1RuF0ltoMeb74hVZVNhUTzrVBYandEIVzw0hbpgiR6191maS7rSvkuBvvJBxRSq2v4YxlEBq0fFsU3aCl9h5HOHPtQ4N8W5S6BMApnFKC5HKE0y3gyLxeYqRXOEUM2bSltqpwRh1AZ+gmEoNM11Y4vaV2WkqtUzgXHAPdIvRCa8dWNXOEk+Sc5H1phdMSziWcVkaVc21R2rbUTiecsVc4J4cGaUj0TzzG/F5pjZIpjbvPHqITSWS3/jnoVz4X2L3Hvv9oDacjYbUSjp3CKS6YzY211FYUzsBS+w3nX4nf7PyP0TpOX8NpCWBDhNONQRnF5b+72siZoUHBMXGWWj3eUjtCoheBdo4LaVJqw32d9rJKaFAXKSjZ8u7FUmhQiXCOuZfNWcNZGueZcDKqSJ2lNpKIowUUzrRQOAFALdE3qZpSG9p7mW+uFoXCuSGEc8NSatNc+dAQruFcLRYJDWp7gPKW2kjimK/hbEbhbIpc3R0SzgVDg7yqJiRIOEvtAoQzsNQm+XyWWtVCDafyRLqw1ELl6MURhrnyFmBy05cJE7txltr9YY4HLgThKp5wLq5wVt+jNlw4kiwUzrlqOPVy47ebvixDOKUlSYpEu6FBKkNKcREaNG5fxoYGBYokKWgI9OMT5gFHhCzuPd9Hrgnf/HmPwk10ypzXVTtosD25lMI5+hTfFsUqnElgqd3Re3ikeHAM4XSra1bhXDQ4aEofTrPD9vO7a80TzkmW2mA/3TGstEXJSCKGwnAJ4cUjUDhTt881bLVuMUoKExrUQwod9fw5JG0NZ6zT8nx/Yg2nxJCiWu8fLpRdLgvnTDjngFvNdKFB895kBrmp4dT2sKt08VQxF2DkiKYKbhrLJs8xloOrLyROqW0FeV4M1JeLFWVdEaH+OaSXDGipCzf+mdCgBiy1QQ0nGiBXudK4b9fsV5orr364tii1CYQPDRKBpXb+z5nmGh1LOGNVT+F0tt9cJMU50BB8X83AUgudoWcVzsym1CrbvmBiH07Hx4Kv7Ff/7nZ84yuLkB9a0lKbjmlPVhdUSe00rW0WsNQuqnA2YKmVZFp5aMiWQ4OG5T6cYxCPhAbJ8nVvCd2BOGZ+H1wsvf6O0yah+Z8+5QY88ZhzRmTln2P6etZa9HSEE0bhnNgWJVA4O7q8MHJC9DHo75Vf5Gs47WdamnC6BRTzMx0hnPY4LJNSa+vNM8RIkDekcBYhZn6fa7RG8Zet7cNpCGfXX8+xTalNaFh2SkxJqf3991qr9izCG1x3l0sWBRPOOZApjVia+s1IirlrMPvDDCdEH4fJSQCAHi5OON1Ngms41w9+5XPd1bcNtdSWJpgbtu+XGqI5FM6jWuAoKZzeUrvEtejSQEXcyEr0/bsDP24Pc+0nJn1vqZ0vpRZS+kncIp8zC1Jfu3pQizy5Ppza2ymbu+d4ElhSOFP0ElPD6VJ1tQ33mPSZxymcu/0MF/rFQqDvZbrgOOIWfhf6+G4cc59z7hrO5fooe0vtMqFB0ICIoCFadS4IlSFFjCl8c0JoUJkkKJI4gCVLwzLhvNPWbz72mh18xpWGID543hK8MX04fT13nfHMLipdJ3YhxPj2dWbvpVcPO4Gl1p2n+cUHyy9y54AjgHkzhLMISquEkeVVS+2kGs7g81VTagOFM4JuuIZzPkstoajh7MQSPZFCRVv+mpBCAHEPMVXaGE7pw3n6wNmPZyicpcUQJpyMCtJcI7ExaYv04cz7ZoDrd64GAKgl+iYVKbWjK6wscK4QRMWK/yS7ybpgQ1NqVWBVXqbZ/cbjnncCd75lpbsQzRHe5IlEyxHw7nQ2oUFNWGrtGNtQvaKz0wKuhrOcUlvXmlhqi7JkaJCridzGoNYE0BFOJSo1Xg3ApdSKUg1njm4kMMiNwhlDQUeGcE5MqR1Tw6k1le6V/hgumFKbWjvgQou87rtyltpV1XAuSThJSGMFbXPSrFOkSHyvzXEYCQ2S5dAgQRoaAgfCkqXBheLFd9yM7K534MrtBFfudHCNTZO9cGAt5uP6cGKOxQqrcHZFhhs643uwm3pY4e2xoaXWvRddrAQdVWs4Fy3TqhJOp3RWF7JGLLV1FE5nSy7XcGYkkQjVaA2njBKkVN9S608VSzi3MISKun7MMDWcPSR6WO5KMUXhPFDO6j99/qeDdkZsqWWMIFOEJDKDWiTE1DCCcdB9M8ANu9eY35chnP5m6n4vTljuw7lCBBPbtU+p3VBLrQ6syotOFC8J3PxS4G/+8+renwixn3TVGHOOWuEM26Is855uEtaQpbZEOFWhcOaya9+uJuEM/WDLhAYpjcSmvu6IwWjrhbHvbZ6jWyCc2tc2OsJp3mM7AYa2LUoicpC11E6aWCqvcAbbJiqLXna/F7XmV0tb5oInnPYYHnENp9vlkZ6Tc0DaVh4astXrWrg+nDUstf7jiAoJJgUNiYNcAvFWmXD+5YvxRXf/Kh5zjSF7vaFpi9LvV/r4lginDQ2aQ+EEgEd19sbOHX1KrVXuYyrOaz++7j9UftGIpbaeJX4EE1JqtbCLIe4cq1pqJ5Gq8Jz0KbXlGk5X65hlDfQr94QzLhTOWpbaooYziSR6yKBkz8+vXUptrGdYaokAECAic34B0PkMhbXUYufymLMz4ZwDqdLoxOYiWcRSS5Zw5tvXAgB0unxokCOa4RyFazhXiHAQWXdLra6vTq0TQkvt5VL7MBYqXa2KPm8fsSMinG7yX2qLssy16CdfEWQDE4O7z5kkzE4kSwpn7hS72jWchRJIjrQscC2HNZzbGNRSHApL7fKE80I/wy/9zW3FhM7dzEJLLYCdmDDINXJtajgp2bJvPX5//eaC70zpihrZQFsUsw8LvFiXJ+AQ0Vz1sKKiRs0Ld51ky6TUwqg6uk2FU2sInSNDPF3hFNP7cLpQnn6mgN6JsqW2fw5XpA/isdca4tYZGMI5GDjCOUbhnKckJUiPvamzP72G09Uuj6kXlQeTCGdTbVGcYu8UTnNuelfRvCm1cW9MSq2t4STzOZsmnBlcaE/9lFohBDqRUaBz2fHfTyQlEHcR62pKbZVwFufcviWc6XD6+4cLi5fLwjkTzjmQ5hodp3DK+UODyBap6+3rzO9LKJyZb4difg8VTuabK0QwAIuNsdRu1mDHhNOC9GrV6XCyMUdKbdvfmXN4dCVhR9ib/hLnuKCCXDVhB77n3CFuunIL3USaGk47SVRyXsJZWGqLGs75P2cWpNTuYICDYX17dBOE8+aPPoSf/X8fw8dtaIurYZVe4bSEM9IYZsrXnHqFc1INpx6tryQqW2rduTjLyvrQxfET+aItyvznhV+QDGs45woNcnVky9VwLrNALUHeUtuaLdDeR1NKIKfMWONoXGhQmbQpSEM4uydKoUHUP4/r6Awec/UWoHJE/bMAQsI5rg/nYgrnw6IL49uikDmW7nwIt+vOz+iwQjh9H05nqV20hrNck0iqTDizzBFOp3DulN9/ZHt237evHtOH0yqc2hLOtAnCaceMOFlI4RQC2IL5jjJZ1HDGLqWWUhDpwj1YSfX1v8uAcM4QlMJxnhVOxggypZHERQ3n3LUPqRng1I4hnEtZan063mgNJ1tqVwi9QQrnhlpqVc41nADMRHuF351WYfhKDZLin9Oywmk336Pghr/EtegUJBLNtAC5+9whHnHVNrqxLFlq1YKWWiGlaXIPLF/DKYboZ7O3oZ2l1tUfLnEeDnPn1nFlIvY88Sm1prZ1JyYMMuVrOJE4wjl+YW9cj2o10VI7+fy96+wBPven/wbvvfv8yN98Su1CltpyTZup4ZxjO0un1Jqf2aKWWjL5tC6ltrWxyJK1dEYfzrEKZ4kQmRrOfpqXFc48hcgO0REKn3K8Dxye8de5V6mm1HBKqnHNZX3sJaaU6lrsjs1XMqRS+POexryXU149qpbapRVOKv90aqS75/oazunXnt/e1lVBSm25Zjm1ltq0QYUzihMMfWhQje0GNZw9YZ6fyU7RLsWm1AJAF1kh5lSvvWDM2s/NeZjNUjhLltrNmoMtinjVO7BJMApnQTiJDLkTUwbBEGJgEs/Ulhl4aNHBAWFoUPHzedHNuA670PTshbfLWBKlQWRDFM5wsnXLKwAQ8Hnfs5JdqoVgUn15E06FsTOXI0KWZ+i6X+ao4Wx7NdetWidqP3jvZRROu9rfUGjQXWcP8BmPOInbHtwrWWpV1APy+hZJcsRdiMJSu2Qfzh0McKaGpZYatNQ6ldARQ/L2OGepNe+xFWkMc3Pv6yBHPiMps6jhLAfqjQv/mKbOnTtIQQSc3hudQC7Th1O4/Xbf3dyhQS6ldrFj/0/z/4ckOoNcf/5Cr/c9G9u21Fqyl2F6H86oGho0Yqk15Lif6rLCGfTjfGxnF9grvsthOqWG06ljNRXOvfgqdLNdXEm7Eyy1VLLUijHv1R0hnHY7PjSomRpO7ZK57WJP7hROn1LrFM5Jllp7bm5fCTz4IXONOtJuFdyhsjW3WQPzpNBSSy60p46ltqjh7Nr5Wia63iboQoMARzgJEcSo4h1aajOn3M6Y34fixGUSGsSEcw5kKkipDZoMOyvHLESZVTitpRZL1HBmvnazWMV9jnwXHi7OLLbaymgGwSAi11zhJK0gYOqxvNXhw68DINaacOrLsGHyWOh8pXboLMsLwlnje/AhN22HBtn3SfKD8MGFt+cJp1y+LcqFwwwXBzkedfU2OrGt4bQr8TruAkPUb4viLMpCAmKJtii5QlcUNZy1LLVuQiqbJ5yuPlSIsqV2KybfhzNGjtyqLJNKF8gTzuIxTZWWFPZzSOiJi8fTrKdZPmrbrY1KaJAQEWIxD+FcTuH8AvVOXB+dwv6i14ZvF2QttW3NO+z1MUvhHA0NKqfUwqbU+hrOi/eZx50CB+AGnAb2C6LiFU73XZXq7twCWr0aziE6OIcrcVKdHTtHM9ubRDjN/7fSSQqnJYBNpdT6OmpzbuYjltqaNZzbpiMDBheMGioT418FMLTEUNWwvs6E3Y84TpC62cwcfTilEOhaS20qe4js55cB4ewhhdKEJMKoldadAyLChUwCEsiyWTWcl5/CyZbaOZAqQsdaaqXv+VR/kI1To3DqY7aGc9GeSRhVOJUmdJEigp47PbdJDDKFn/qzD+NguN5kqzWUBpH1Vt9OXTCrofefD5QgrZZSg44CpZTay2SgHgutVmqpDScKtb4HF3LTtqXWK5wh4WyiD2eEekuLk+ESah9xVUA48yFyRBCWWNW11PoekkICTg1cYAEitLRti0EtSy3lZUtt3X0e+/4VWypV26LY99iOFAaZhlI5IkEQM4JLHPEoKZyavDPJvJkNB4GeWMvoHh53r89UmSzPA0E5FCR8YaKzUs5Zw7voopOEUbYXDg3yVvOWLbVWqcpqWmpVKTSoXK/rLbUTFM7O/v3AftHrMksrhHOJGs4hEpyXV+KkPj++LQrItEUZExrkxsxjI4TT1XC60KDROWWaa3zBz/wt/vIfT438rdhOhXC67VqF05ex+NAglxA9iXDaD+gIZ/+8IasuIAvAULmU2mz5MjBVWGrTOSy1YQ1nlyzhFB0/doQKZ08EwUETQoNICFzMLDeYUZtaDg26PEQiJpxzIM2Vt9TGVftGDcTZHjLEQO8K88CClloiKupdgl5aHZHbldqFNtsI3n/PLl711jvx7rtG610uCwRkLaJ8rRODc2eLCyeLpNY+RCickNWqn7lUQaslnHlATGpNutx51rql1vyMs4BwLrOIEtRwzmV5HANHOB/pCKet4UyRIHKksea+kp8shaFB818P4cLBDoY4rGOp9STcvO9ShLNqqXVEuhIatBVpDHIF5QiyVVkm1cqPt9RWVE+73xH0RGdQUQs6+hmHS4YGKZeoCXjiqdSchHPBMUBAoyPG36Ne8aaP46On9qZvwI7DhKjd0CBVhAZNs9Q6p9nktiga2oUG9a4oajj7wVzlwr0Vwjko7cO4lNpaCaP5AANKcCG+CifV+bGigGsx4xVOjCGc+fmyWyNMg4UYGxrUTxXuPd/3oVxjMaJw2v2z195oDecsS21QwwkYUq/zol4ZwECb70tStlRScrgfcZwEKbX1+3AKCCS2DU0qOr4OWIr5ajhzkr4PqJqlNoflV5eJU4sJ5xzIFCGJBaA1IjF/wlsn38Oh2IZ0q0ML2h8c2RSiqnBmRuFcIeN0A+mgRvPwdcYtd5yt/92GtXTBABxD+cnUOsIpCSWCuQEKJwVhNcsSgCOF1ktZO6sglde2X7YBFd7Q66TUOgtay9+Zb9pdstQufpxccqgWydIr0ffvmgnhw6/cQieSGOYKyIemPs0SztrkzROzJQmnVXF09wpsiyEGwxoTNeVqvMwEcpnzcMRSaz+DiMqEsyfNYupwaO6bslMvpTYcxkdUz8BSO+mwu+eOmxT7tigLnBZG4QwJp/l/ntf8DpdMqZVkamGroUFaE17657fiDR+8f8b7F6pOqzWcQWhQNGXGOr4tSjipJ2up1YZwZoeGSFpLbSq6lnA+5ImRyiYrnK6eu1aOQD7EgBLsx1fhCnVuYg0ngpTacfWiMfKSIluko0ZGdRxDON1CytS5yAjhnKRwzmuptYSzv2sVzqKKb2BTamMoDPIl72OOcCZBaNCsPpgoFu2kBLqWcA7R8WOBS6kFCkuteWFV4bRjhAY0JBSJYmFs0nuXFs43aB6zBJhwzoFM2dCgt/4snvuubwEwJ+FU+ziUxzzhFAtaap2dthtLEJkbRK61J5yrrOF0BHi4xkRrFu44vY9vfOUteNPHHpr9ZJUBP/tE4EOvNb8Hg0gMZSaUawqqrM6ZBzdA4dzUtih/+K3AG/59Y5s7s3eAs3uL2/KXxaIKZ9vfmQ8Nys2Kfiq6zVhq5fIptc4+2o1lUMM5RIoEcTyfWuivXymWSql1CidtXWn28XCKEuLeu1J/qBuw1Po2Ju48qVhqtyLzeN+2qhAzFE53HoR2Pff/6sQxgi61Fittxz48toZzGUutVtCiIJyuZlXX/A59ycYSCmeC3M8nHNz8YeY8IrCaU6uWWpseimhqQOPs0CBlFE5nqQWMrdYSuPu7jwUu3GMUziseDgDInfo/1lI7x3iWD9CnGIeda3BMXxh7jxWVlNpxbVEAlBTYMKwGcW+sa86dm/MQTm81tYs9fhHEhwY5wjkh8Md9Pl/DuQscnvH2VADoK0c4NQY1XBUXDjPfnWF0983+JUmClJyltn4fTikEOjbVfICuHwuiSACxSSroIiuU6RHCafY/tapthrhYrJiEMefSpQ4mnHMgzTXiSAJnbsfxgSk4n+dG01UHGEQ7iDv2oquxAjMOLjCol5gblLK9xTrIIIVe3g+/BNxNapMVTheacXa/RjH7cA84eAjY/YT5PRhEEqi1Jt5uYldKxdR6pTbNOqBgQrZRCue5TwDn7mhsc6TUUhP9ZZGHoQxzpNS2bal1Y3JkLbWD6NhS57Sb+BlLLS01vvq4fSHQjSNbw5liiASRnNdSaye8IoKIllA47cRIbJ0EAOTDGVZKBJZaTziXVzjdYqVbUCr6cJr36Mky4Ywc4ZxwvCa1RTH77z5HQThnKZzjazhHbbt1IXUOFeQ2irkVzuUttQnykc9VhCTVfH8hoUWboUHWUovEhzWOw0hokKyGBjmF04YGAcDwglc4T209riCcJ24CAOhsCuH0KbX1FM5DHWPQvRoShBNqd+QpclpKLTQOyEa0hYTTt+OIDAkc45rTtRRO59AqL2IIS7byEUvt9IToEYXz1D8At74BeOJX+ae4lNoYuflOpiBXGs982d/hN9/2ibF/dwpsHHcCS+3s9NswpTbWZhwcolPcQ4Tw9ap1ajgz+2uKeGYYEgXWee7DyRhBrglJJIB03w8y86iJW+oAA3kMUSQxoARiwRpOFSicgLmhKk3oCmepXWizjcBNqIYbTDjdd1or+MhZWNzAG1pqRY5htr6EyFs6aLMUTneMM5FsVlsUnS28yDQOktRKV0ZVMDGuU8fkCVLbllpXw2kttYfR8eXOaVIgCN+Hc5m5gRtbIiHQiaVZkMoHSGl+hdN/UCECS+38x9ZN1oRVOPWghsLpJksuNGgJQu8W5XzNpa6EBllbX1eaxwcDcw1JG5QiJkwsi3rNsIYTpfcSgaV20r3cE7AxDCz1NZyTP98kCMqhxGgNZ+1FJHc9LRoaRBodZCPKrvt1Jol2C5Y2pfYoQoOm1XBKTzhDS22ZtBmFU5UVzv557GMLF7o3mnrOc3cAx6+HEjF0Pi00yPy/1qJnPsChTjDsXQsAuEKfG3mKt9T6c6JMbk+RJW/7gfMqVHOT3ti2KF7hnLaCUFkMdGOQdJb5qqXW1jXWruF85yvNz2f8W/+UQ6sGJlAzCeeDe0OcP8zwvnvGZ4O45Po4CUKDatxri9AggcSGBvUDwhlXU2onEU49qnDSrJTcYO4i69QBXwJgwjkHtCZEUgLpvm95MY/CuaUPkMbHkEQSA3RqSf7jMKJw6kLhXHUNpzsegzUmWrPgjt9BDZuHJ5xuIC5ZavVaW2qLPm6bVsNpCSc6mzVQq3TxxtxjIKFWWvuhSmnBs8ccN7k/KkttlO0jQ7y0pVaShhYSEMIQzmX2LWgoHoYGDREjtjWLum4fTkeWRFTUfS3wOZ2K4winqkE4/ZgxZ7LuOHjSNsNS6xTOooZzusLpbs2ltiiVsL3CUktTUmrHK5xEVNiBF1E4K4TTfV5VU+H0CzcLXk8ShI5QI0TaW2pnzW2c8g+TUtteaJANc6HpKbVFqzr7wJg+nJqECcXyCqex1F7EDva3bjCP7T8IHLseWsQQOjf38HGhQXOm1B6oCPmWIZxXjiGccqQtSnH8BTQeoiuL/XMoWWq3plpqq7W6JUyo4ZSxrWV1ZSxuzhp1zSLXJBXRbS/ZNoQt3Qc+7fnAyUf4pwxy22IQauZ88V4btnb7Q+PHJncv6nQ6QUpt/fm1QKFw9qkgnLLah9PtZtXO7hRO+3CGGHom4Rw9ly51MOGcA7kms+KRHkDQ/IRzhw6QxccQSYEhEsgFJ5+u5qIXR36/chsaJKfEu4e4f7ePv7u1Ro3inHA33rUmWjPgJiX7tRROu6JoJ3phj8gY+XpbasdZsjZB4bTXXi6SzSq2V00rnHqlNyo1bz9URyRa3ufQUnsotkwwy1KLKGRq1CAhQUst6Ckir9J0o6ItSkoF4aytWLnVeSkhlggN8iqOJZzI6tRwOoWzAUutqlhqfRP3cmhQV5j3GLreiFECBQlB4ye9RQhRqHBWHrPjhxSTF2rdJLNKOPMx250Hgio1nJZw6kmtJqpYMjTIXbN5ZWI8zoo8/v2dnbNthdNZamNMETj9dVVSOHWFcEKYcp+SwrmLXTqGw60bi40duw5aJkiQY28Q9jsmf9ydslnHZUP5APsqQb5zPQDgSr078pyiLYqw+xsqYBoXsGOEir2gvYknnGJyaFCdXI2Rtij2s8Xl0KC9A7v9qGOu/VkKp5BA7yQAgb+88hvxH177Af+UQ2upTYQyqvMU3GfD1u48c1AQ58NzwH3vLe1fFFpqa/XhLEocYmXm433q+EWXWBYptWVLbVXptGOTUzgpnkl4y304mXAyKlCazApbeoCIcmDKqug47OAQeXIcsRQYUGdpwtlNKpZa5IhqtkX5X3//CXzP775nofefBjcWbLLC6b7T+Sy1lnC6n5DrHxqky4MlgLVXOInI99zKJSucq7TUllZwa002l1Nk6sJPIrI99LFleh0uSIiICIKUqa2S0qSZLlPDSYUS40KDSA0xCEKD6loqi/YhBeGsTVbC7bjv0dZwIj2Y+Fz/morCuVRoUO7aM7n6SjvZ9Qqn+WzOUjt0rSqiDjQiyAnf7XhLrXvMP2A2NWWhdpLiFypGi3x8qXNoEdRwWvJZty3KsqFBbrGOKuEmI8FKkxCQCoJsbyHJKpz5DEttQTgDm+k4S22phvMiaLCLXb2N/vYNxcaOXQ+KOgHhDBY1vB3bEc8Z35fKIUhhQAnkjgnROaEvjDxNkLaWWjGiGEvSUBA4TScrllrlX4PusaLVS/j2C6TU+nZBSdd+hBy3P7SP33zLR81YGMXGeTCrhlNGwDWPBz7t6/HXp0/iL/+xUGcP8yCldoal9t7zZp6VKcJdZ+0i/1t+FvjtrzW76/pwRjGSSCIXSb0+nG43hUB0eAYZRTikrl9Mimqn1JqfjjeniEH5jBrSkHBuUhbFEmDCOQeUVzjNCrCch3BqhWPoI+8cR2wttWJZS21cWGpzpdEVWe0J0f4gxyBrPmDoUggNcp9hGYUzFR0TGrTOxNvVSlV6lTXZuqNpKE2I7A3+clc4I1IrDU3K8zlXaI9I4SwstQc4lNtLEU5NhoyQJQMCy2UeaU1OwCgstXlqFE5LOGsTCF+/JXwLkUUIp6/PsgqnGI7WgY2+qFzDuYwrolrDiQk1nB1hJ3VDRzgTKBF7t1EVXuEsWWrtz4o6OI1wuntkNc01nMAvZqlV0GPaoszbh3NRi7q7DqvWP69wzqzhtAsFQrbbFiVUOOsQTrfbFcJpQoOksdR2rzCPDS6CDs/hAnaQb19X1E8euw6QCRIoXOxnZSWPyuPYzONvFxmHSNDrdUvbCOFDg4ARxVhYl8VDdAWoaqm1r8GJG4EL941s1y3kzNUWxZHpQOG85/whOsihhb3mZYSJKbWh8votrwOe+wrkmrA/zEFkgtcGVuGMatRw3ne+UG69rfbBfzQEWytoe47IOEEsJVRdwulrOAF57zvxj/RoDEn6Y2YIZ5FS6y+JCW1RUueGQAzo+pbajQo/XAJMOOdArsnEJNsV4AR57RuNGpiVJ9U5XlhqVXMKp7MP1A0Nchd405ZP34dzjZW9WXBf6VwKpx3wXJhGLjpW4VzfgYT8zSXYxzVXOHNNiEPCuUkDtcoaVjj1Sq042jdkj+qFBs1hQVtqv+wpEWX7GAhLOBd8T6XJTARtuwJR00EybXtuYtyxllrKTVuUJHZ1mHUJhyVmQhZ2zAUm/eQmZpZwyrxGDad7b0sGF3lfh2ofTjeGFim11lJrFc4sLSy1WkQTzycvRoxTOKuW2ikLtU7IVJWFuDCEZRHCGSGHlqMptfNbahet4bRJw5VFMFU9RhPfP1A4hWivNjvsw1mjLcr00CBrqa3UcO7SMXSSDnDCtEPBseuBKEEiclwcZOVaxeCcCX/O2v8hEmx3krGvITLjjCOPWsjSYqq0+36aToL2JhDOKx4B7J8CZYOSs8qpdfPUcGqvcNrrW+W4cJgZwukWmepaaqMYiGJkyizqDHONYa699TWpo3DuHuIJ1x8HANz+kE3RPnOb/YADX/csoxhxJJDLTs0+nHY31RC47z14L56ENNdlhdOm1HZrhAYNXSyGTCaGmRXvHS7YbtA8Zgkw4ZwDSmsz4FnCaXp31bvRDPfOAwCoc8JYatFBtCDhzHwvN1fDqaHtRHbaSm0Id4FPTS5bAO54XBqW2jqhQRWF0yWoyi5isRmW2lLN2JrXcKZKI7I3ayW7G0Y402ZrOLFahdMRzgxxzT6cdjW57RpOtzqf7qMvt6FILhwaZAinVTiFtORzyRrOiqUW+dBMpq1KWTvxNajhlDbhlBZSOB3hNImSMp+tcPrWRN5Su/gxqRJO7chsxVKb2HM9S+3+ygRKRJATFE49RqnzZMpNNIO2KLNCg7IRS21IZKd9wvGQlRpO6VNq61pqx5RE1IQnOMBImqY7XHVrOH0fzpZDg7IlQ4OkreHMFBmyE28BgwsQgwu4gB10YglcYdqh4Nj1EHEHHeS42M/L90R/vMlvdyq8wtnBVteoZdWgK02AEAXhrB5PAQ2CwGm6omKpDQmn2fff/Mu344v/+83+KfOl1JZ/xp5wZtg9TNFBBi3NY4iSyeOqb9dSUAwnlOwPTXp/bglnXFPhfPz1x/Dwk1u47aF9YLgPXLzX/DEbBAqnsdQqEddSON1Y3jv9QUAN8UFpCKcKCWfUAUGgK7KZllo3ZaQogZj1/nb+ZRbOl2u3tSlgwjkHlCYkQvkBJIaqbakdHhjCid4ViCOBISWQsyT3CcjtJOh5F34DV+OCOW9zo7RJ1LPJuiLtpi2fvi3KGit7s6BVih+Jfx/UPz/zuSo1k7P7zu3Z19owKdlde4WzSFrbnBrOLNclhTNa430dgavhbOjGEkGtNjQod2nBca39cBPktldz3fgnsoNC4VxwEUURWUttkVK7TNupk4d34zvF6wAidGKJXFOgcNq2KLVTap0drKjhrG3HDKHKNZxxDcLp7dGxS6ldPjTI30t9Swar/llS2xFmUun720UdaBFPJJyFUhfsNpX/hoBwTgwNmlTDGYzt82Q5OEgq13BiXoUTi19PRIXKRmrR0KCiVlJDtt6HM0PsOseMhVM4dbBf4b3MkDazAVPHacibyAe4SDvoRJZwigjYvhoyNi6li4OsUsPplE1Xw1mTcFKCnV4MDTGGcJIdQ81noMrxlCDIKMZpOgk5OFcE4mhVVjgB3PyO9+HUxYEfH+r14SwvXvj+tK6GU+XY7WdIoKBKCueMGs5gQcW139kf5Bjkqkw4p4QGaU24f3eAh1+5hcddd8xYas/eVjwhO/QLbVGUIJYCGepaas3P7v3vBAD8Q/QkpKoolYulCXHSURc9pMXcumKl9aFBjmdHnYlhZg7uHNAiXvq+silgwjkHlCZsUaFQxFC1y92yQ2OpFd1jiKVcSuHMlcYnifvxT879Lp4pP4Bca79KOa+ltmmF81Ko4dze/Ri+J349nng4O1RpcGDsZ/uH5rt0A5+OrKV2nZVeXRk0gbVXOHNNgcK5QZZarQCQrZFdvEWHBxFi6BUrnAXhrGXrc8pV6ym15qdM9zCUy6XUKhVY3YREJJZLqX3S7pvwffg9YHjRO1TIptQ6S22tRvKA/0xSSJ/ougjxI2f96uwgFzESVYdwmu9eRMv34Ryx1LqWDJGdnljbbmJrOGMU6qrGZEttoZgGSmQlubZQOBUm3Qp9W5RqDWfwgkXUCUkKFBBOR7Cr1t1JEFWVZQ7oQOGsui7mreFsvw+nVThrhgb572mkLQqZxScAA9caZfduAMAF7JgSpU/5WuCz/wUgI8jYhQZNr+GcGRoU1HCe6CUjZBIIvg+r0lYtyoIIUka4CNMKyOWIgKggdVbhvEYZBbS6cDCdcFL5p/1uk44hnJTn2D3MkIjc1EcCZoFkVluUQOHMKgrn0LYv6Yl06nzx9P4QqdK46cptPO66Y/j46X3o0x8rnhBYaqM4QRJJZLI7tidpFe7a7tx3C3DNJ6OfXFlSOJ2irizhnGipDRROIQBEHUST6lv9mxcOgVW3MzwqMOGcA7km9FAUL0dQI02TJ752YBQw2XM1nB1ECyqcmSKcgLH1+qhmZ6kVVCsxsG+J0LBhYlj04Vxf0jILjjRSNntBYOh61lVCg7TsIkGOYcOEvklQZVUTgCGha6waprlGbNsjKNHZHMIZrrY2UcdZqSNaBShUHmrtx9EonD4IIt3HMNoZUTj/8N334Jf+5rZJLy9BkbXUIoJXH5ZZinZqXHpgLHyAtdQWKbW1e1q6CYqUEHPaMUtQhWKYyW101GhrhdG3Nj0NlyG6Dmk1NGiipdY83gkJp4gnEk5HAsN53GhybaFwTrqXT6zhLIUGTfp0kxFRpYZTzKdwLuMY0FQodFWFc5KiO4JSSq1oPaV2Vg2n46L+PJJRhQQbSy1gF9y7BeHcpWPoRBHwpK8CvurnzcvjDjrCWmrVKOEs2qLUtdQmeOy1OyAx2rPUKc4UWGpLKbXQiCLpCbMfzwJL7Wl5DQDgEfKsedvKgkuqpnw/1RpOZ6m1oUFaF5baQuGcYqkdQzjd9XUwNArnIZl2IzsinWqpvfe8IY43XbmFx193DINMY+/eDxdPyPogS+5klCCOBAZiC0jrEE6jfCf3vwt45OchiYSvNQWA2I2rsosuplhqXQ1nDmwnEShKIGcQTjf/Mgvnyy1kbgpqE04hxK8KIb7a/v/VQoi3CyFe3N6urR80EbaomCwmULVPkqxviEnUOwYASEWCeMGU2lxrHBfmYuphiFwTRFCHoWvYqvqpTVNtmBD5PpzrrOzNgDt+VIMYZH1D/F1Sopss6thaateZePsJS7WGc32/uyyo4TRtUdZ3X0soEc4G6jidwrRSS625oeYiqTXpFUeYUiugIbMDDOU2chIlwvlXH34Qf/qB+2ttS1lFnWTRkH0ZNc/XSweEU6gUKeLCUlubcNrjKWVhP12ScObxFraoP10NAQBSUJA+2GeZGk5XduDbojhLrSxbap2y6Sz1kAm0jGyLslF4ohjWcFaTa4OeipMO++QazuUstRGUTz8GCkW3zv0bwIgNch5ou5ACjNZwemfzrLlNWMMpZHsLSWGt+BTCKYRAJEUlNCiwpVJBOA+dwrn3AACrcMbl6bCIOtiSzlI7WeGMZiqcZrw/trOD41bhrC6SkFsACEKDwuNpCKfxtJgXhITTfKZf//v7cZquwOdfaxaMqsp8Oi1PYkLqamwVTq0UdvsmNEg5Vb5uaJBFVeE8gCGcV0Tp1MwP1xLlppPGUgsAw1O3Fk/IB0VblDhGLAWGolervROI8HhxH+TwAvDIZ/i6el/DGVmbdtxDT6TmsIQDReW4DRRhqxMZhXOmpdaOeyKGFMuF0W0KahFOIcQXAngYEb1eCPHPAERE9AwANwohHt/qHq4Rck3oUqBwisk2nCpSa6nd2rnC/I4uYr2gpVYTTliltYfMDCgBea2z2uxTahsmhkWT4TUmWrPgYvnz4UyrVD60hFM7wmnTaqMNqOEMV0nDx9ZY4cxUkVKrZGf2zX5dEFqPmlA47XcXrdJSa8/5XNSr4XQhG233HFOasAOrKkQ7plYoOKeVptl2weC5UhCAgnAu03PSX2vpPrqRI5xDDNFBbNXCeduiSCEhXQ/HBQinT1OUMfJoG9tiMLMRO7QydXuOhDdQw5l7wmnPbWeptYpKbIll4hXOmjWcwXdNFTLlFtsi6InnhA8fUlXCGW53McK5TA1n0ZZj/vcOCWe1QX39Gk5LvGxblKYJ51/94yn8h9d+AFAptIigIadaagETHDQpNMgF7wCBwmmP4QXaKRwHfmMJulLbtiijfTjrp9Sasei6K08CALSIRsZAX8MZtEUJnyNAiKJoqsL5po+exsXuDbhRlBVO34dzntAgO8YVhNNaapEjFzY0aE7C6c6nfatwDpGAhMQJOZyhcJq5rqvhBID43G2mBhco13DGHSSRRF9s1SKcmoCnSUteH/l5vlWVO2ZOUddRDz2ncFbbyAU/h0qgl0RAlPjxaiKCBZtl+ztvCmYSTiFEAuDXAXxCCPG1AJ4J4A/sn/8WwBe0tndrBK0JREAvIJzJHJba/oEhnFdccRIAkIkxltpzdwKv+AJg/3Tx2J/9e+Dtv1x6Wq6oUDi9pXZOwmkbBjVew3kJpNQ60tih4UzCqGzPOqdwenU03jJ9ONeYcPrG8aUVu/Wu4TQKZ0g41/f4llAinGuucN7198Cr/0kRTDEBZOtmVO0aTqeot61wAsfsglwabUORKE2Mck21FTlvqRXSqyvLkCtPfL3CSZA6xXCBlFofqy+k78NJi4QG6YDAJTvYwRCH2YzJkjYKZ0E4F78OqzWcfsGvEhokdI5uLE1wHwBEMWhOS+1Iyw9njxSTe2q7h6uJ9MtbapW3CwOFolt3QcNbahdYdHP9ZQFAVBrU17bUuj6cJtIGaHgsuvljp/En77/fEk5zDkyz1AKmjrMIDSo7GwyhM9eJr+G02MU4wtlBVyhcHOTjFc4K8QQA/P4LgX/4o9JmdGoI58OuNgSJKi1PgGABwF1PQpbGdqNwBoQzDPyTEXKlceeZA6Q7N+LY4JTZpq9XNk+drw+nc0+4ULAcF0YUzmg24QxSnnLlLLUu20JAxTs4Lofm+5iA+3b7uGqng+1OjJPbHVy/E+PE4d3Aw55inpANfHmHa4vSF72iznUKNBE+S94GvXM9cOWjTf2nqrRFAXxokKLphHOQE7aSCCLqIKbMf+bxh8gqnN5SO3N3Nx51FM5vBfBhAP8dwNMA/BsArrvsRQDXV18ghPguIcS7hRDvPn36dPXPGwl3o9rSYQ3nZBtOFemhqeE8edL0OktFBzFVJp4PfQQ49SHg1AeLx259A3D335eeliuN43CW2tRYaksK5+wV0kFLCqcb7De6D6e9SfVEiv0ZvThdSq2zyrnXUtSFFIRhNqNwfJUYW8O57gqnRuxDgzbVUtuEwmlXdNv4/A+8H7jnFmBwYerT3KqyqtsP1U+Q2/3OtCbsCHOM03i0hlPpyWrWuG0ZS20UKJyLzwy8CmQJZw/mvOhT19ti64cG2QmvjLy1dSG7b2Cp1ckOtsVgdksoMgqnm1A2QTi1J4hWdZTBxFZIQGfoJVFZ4ZTxRJfDOKWuqOF0n8O897TQDuUJWPkzliy1C/bhDC218/bhXDo0SDiCvyDhDPrAUgsK594gN8dYZb734wy+iUiKKaFB2tccH6ZO4TS4QKOWWsgEXWFDg8bWcI4Szuyjf4mPvPP/lTZz7qKZ+z38mpPm5ZAjQUNFTW2YUlu21MZRBE3jFc57z/eRKg158hE4NngAQLGA4s7NbI4aTk84bQ0n5aaGMxE5cgQLQQtZajM//9SJIZyzFM6brtzyv3/2FRcRUwbc8Onmgbzv70VJHCOWEoeor3BeiT3o4zcAQqATSQxzDWWvbUc4yY4zNIlw2u9joIDtjg2cEgqH00qqvMIZQ2LygtelhDqE8zMBvJKITgF4DYA3A3Df/rFx2yCiVxLRU4noqddee21jO7tKuJOho0OFM6+tcGb9PSgSOHn8uPlddo3kHq6Wu4vX9VnSCjg4PZIElulC4dzC0EyAwhrOGSvwRBSk1DYdGmR+bnRokD1+XWQ4mEE43aDmbF1FSq2xouTpYsFQR4JxoRNrr3BSoHB2Zwc2rAvCa7hGGNUslOq8mlYM3Tg0g/h4S62sWcNZqX1qC5rIK5xZtIOcyhPPXFHthUKfimzr1IBlFc7CUtuJJI7b/dzHFmKXWltz5woVQhbq6AJ9OH24RZSAkm3sYDB7/NbaKJyOcC6xSDXJUuvIgfklAVSGXiJLNZwkpqTUTrHUuvt5nT6cTikdUTgDwrmIHc4sZCT+d/d5a9dwLhHCpTUV1+HElNoZG3ELBK6Gs+GFpL1BBk2AVqknnLMstVIE34UohwZJaESW1Pu2KDD21T1sj7XUdoSyfTjH1XAW5455nJAgx8H+XmkzD57bBQA84jojNlClttS8NEjDts/xNbb2b3EcBwpnQBCFNK1CAGxf+yjEeoArsRcsuFg32xwKp/+Mseuzq7zCWbLUzpFS69uiDFUhSHR2sCOGU8eb+84f4uEnC8L5GKd3OcKZ9UE6R04ScRwhiQT6qFfD6Y6tc2r4Gk779fjzzSbJKo3SOZXlAfEH0M8JvSSCsAnH00oTfFsUGRu7N1tqAQC3A3is/f9TATwahY320wF8ovG9WkO4m02phnMO37Ue7OFQbPlgAH/RhmqHJ5wPmp+HZ82JXEmRy5XGCadwisz05QwVzhk3rCzoM9R8Daf1sq+xlXQm7PHrYbbCicz2P3WWWmczslH+ebbGhNNPnMt1GwA1T2IaQh4onFomhb1u3dGwwpmHNrimFwjcODRr4colM4tkrfpwKiIcE5ZwxpZwBhNGpeuvJittAogQWmqXmVhXLLU7dj/3aQuRrEwmZ8BZ+oQo1LFFyLAICWfnGLYxmFmDL0hBCektiovWtYbfhVeOHeGUAeGMHOGMgpTa2CoP48doH0IUWmoryZ2ONJjQoAkKp3282hYlW6ItChEhImWUcwuvUtdsm7RsSq231FYVTn87qGephXQKZ7P3jL2BHV+yoa91nUU440gWIsCYtihu/lXUcAJZchwE6dsUeURGpfJ9OJ3iXlE4I2iAyH9vIi+nPJ/ZNeVUj7zuavN5xlpqUanhLBROFygURVERGlRROG8/bQjnVQ//JADAjeJsoMybp9YinLoguYAJTgKAQZpCk0mIzkqhQRPGCfd4SDidwjnI/byTOjvYEYOJCicR4b7dssL5CH2v+Y+31BqFUyFCLIVVOHtAdoBZK4suHdjVT3espdbNY/35JiNEQo/UcFaT/gc5sNWJIJMuOsiNkj7xze0xEHHtdoabjnj2U/BqAL8hhPhGAAlMDeefCiFuBPAVAD6vvd1bH7ibTreicNYtgaR0HwOxheP290x07X8GQGfHPsluzCmcjnhWVpFKNZxIzaQo6Ok5a7U5XHVpvobT/NxohdOSxy7SmdYyd3MpQoPsT6dwzqiDWymqE5aqtTaqMzwcLdKghlNLu2ijNaZ2BF8H6GZDg3Q4JjRN4GoqnN5SKxOIWuNIeaLWFoiAYzY0KIt2kFcstfmcoUERyKgSXuFcxlJr92O4j+5J6ZXYA/QQxW5CW3P7vk4q8nZcvcC5UCicHQirONw/YyFSUA6NqEgNXfAcDCfB7hRy41FJ4YwSQGfoxoHCGXXsZG0ArQmyQkY0AVfhIoROgscqqmeocE4KDapRwznvbTTXZNo7BQqnq1mt29qmCA1a0FLrrsPKgrY7DjPdW37CLK363+w4dLFvzkudp74Vh5zhqZUzQoNcnWw/VcC2IZxpYpTOEUtt1EFCuSGc27npB6vzEcIJACANlaWIAcgK4Tx3wSieJ46ZwBtCNGKpJVfDKQuF0y2GuPrOKIqK+5wbR7RxX9z+0D6uPd7FzrUPBwA8XJzxBE9pwlW4iF11DEQ0Pul3Qn9JYecxg4ERNBLkSBEQzkl5BF7hLK7hrNIWBQBE5xi2se/b9FVx9sAk2IYK503qHpwTJ3HV8YeZB/KBUTghEUcCSSx9Ai6yA6B7fMyWDTQVDhYgUDjt7sRe4TSKc90aTmnb4h2mUxaPfA1nzG1RHIhoj4ieR0RfRERPJ6K7YEjnLQCeRUTTC30uEXhLrSornLWbNKeHSKPiosmlJZzh4OQVTlP0jT1HOMs3hExrb8XqYWgJZ/GcWavc4WpS4wqnq+HMNtgi4Cy1Yral1t1cvK2raqldY4WzCA1yN6/QprmeCwaZoqIPpyOca7qvJTQcGpTloxavxqDLN9FJ8PZxUbMPZ0VVagtKE7Yt4VTxtrXUqtLf51E4/YTEJRYuUa9YreE8ZmtN97GFyC3w1Dyf3fgqgz6ci4QGSZ3ZeswIorOD7ZqWWg0ZKKtNEE5d2lYULnjJQuEsWWplbBZ+x91r8hQ3d/89vlzdHOx2uYbTqXLTLLU+pXZKDee8k0WlTdo2BaFBkZxPLV66htMtAOnxfThn7sZIDWc7CiflRWjQDIETsRSFMitskJEP9yGfBB0qnMPYEJJRS22MGBkOUmXGusjdb4yiKQUhJUuotPL3ellZULxgazgRmznBOPuxr+EMQ4OcQhnYbf2ilF8U1IAQuP2hfTzu2mPAFY8AYBROf07mA7yp++/xz6K3TK7jnGSptdfgcGg+WwcZUrg+nPFI/e/I9sYpnGmhcIrODrapPzE06P5dM7+6MSCcN2T34C55E5DYx0oKp0QiBQ5h59czbLWaTGCYGz+TiQpnjLgG4Ty0CmecOMI521JLTDing4jOE9Ef2LrOywLjajjjOdqiRPkB8mjb/567yXI4+XQT/qrCqWcrnHKOtiglwtl0H87gpr2ptlqnUtax1BaEs2yppdissKk1JpxFTd0EhXMNkds+nCSiwo5W04K2UjRsqVX5ESicNS21uejMZ6k9ghpOtyhBUWL7cJZTausSTtfT01hql69X9Mc03TeEE4WlNp7TUlvUkskiYGcRSy1lUHZCL3rHsY0hBtNW5mEmS6YtiiPhix2TYUCQPWl0RCZ0LViFsxdH6IjcP+bsaOO+T6mHOCH6uIp2/WPVHpNu0jetLYHvZzhSwxnWhs53TueWcIYptZ68T6qLq8CN24ss4GhdhN0IVbXUFkRnKrzCGRkLaAs1nEBZ4ZzZFkWK4nsS5etJoAgN6qdFDefAEs5xCqdvbaFzTxhNsJ49J1AsEuWZmYOF7e6ICBf3bVqqnRNASHMPo/L5ExJOBG1RnO2TRIQ4rlznZBK0P/7QvmkZsn0V8qhnFE5nKc/6OC76uB7nJzvaqqFBga1dQWJgsygSkSMLFc6JoUGV7wBBaNCgUDhl7xi2MJgYMunceDvdwv3xsPRu3CUebhcAhClrcgqnFIgjgQOyx3om4XTpwGWF06fUiqKGU2LUUlss1pcVzrjTRSw0DgeT53++htOG7l0GfHMxwnk5oiCch/6xGKq2NStWh9DJjv/dK5zZOIXzwfLPamhQmFIrsjEK5/TJQmipHTZsfQ2PR9Pq6ZHBDh69GqFB7ubirXI+pdYMeHleb/KwEoz03lp/hTNV2isDQhSry2uPEuFcXuEsE86WajhnER9dpNTWmmweYUqtU8FkFCMjWZJrlJ5cr1eFDw2ydWrAspbaQuHsxhI7QWhQ5GrI5iScMggNmpf4EREinUNb4iO7xyAFIRvMCNwgDS2kr31aKB0XE2ypvv4rDA0yASXdRCKGUTMghFU41QgZNJsx52cYKjTSFiUIfpk0F/eW2moN5xJtUZQao3BGiymci1pqixrOBftwBnV6JJpNqVWacGDnKaRS34qjapuuQspAba4s4EirBvYSaUODjMLZj83PcW1RfI9XnQHWtQTSftEpx6jCmQSE8/4LA0g9hBaRL1FxLU/Cw2tqODXclJxE5I9n2KMzsSE+RVsUDUUCe8PcEE4hMNi6ATeKM0UNs8ukEOnkOs4RhdO5J0zdqHIpsMiRuc8cTanhDFo2OeSBpdbNDWX3GLq6PzFcx12v3kp9cAY7eg930I3GcZJsmwVcbRXOSCCOJPa1Uzint0apEn3Xh1NrghDB+SYju0iAyvhctiL3c2AriRAl5v2Hw8mLy75tEyucjCrcxZIEltoYqpalNs21qf0cRzhLCmeVcFqlsxoapAnHhbPUmrYoUXjTmLFPocLZdA1nWeHcACIwDj6ldrbCmdjjHrmUWhekYm9Oao0JJ/kbsbt5rb/CaVJqNSAj31KgbsjGShGmhzahcI6J6W8MNRVO+LYoMWSNm6UPaGn5xqqIkAh7TGQyEho0fw2nWQEXXlFfxlIbhAZFUWGppR5ib6mdU+GUEWQkoUnMvfhglLa8CGXpGbVHD6dP1AqF04WYLHZMhuMstUFtqkfUMYQzjpBAeUXWtStQY6yCRXuZ4j3cJK9qqZUTVFLz3PEELLx3ztvSINd6osJZv4ZzOcLpnAZypC1K8ZypcGqYlFbhbO663h+E42Xqv+9ZfThjKYvvYkThNMRiK4kMwbGW2r60ltpoNKU2ogwC2hzjyJE98rZvT7507u/1nYBw3vbgHrrI/AI0YMhkNXDS19T6YDLhj6cbg4SQgcJZuJJSbV7zSdeaGtH+9o14eBAapAPHVl3C6ecGkYBC5HMTuiIvW2pnpdQGLgXl26IYhbMTS4iOJZwThA/3Mb2yfeZjAICPk6lVRdIrUmoRIYmMpXavpsJJBD+fAMw54BTO0rkmo8JJYT+bIhEcN7P//Zyw3YmQJK72dfK9vmypnTz+XEpgwlkT7sRPVEXhrDHWnz9MsY0hRPeYf0yNq+F0J+/gggkT2h9fwxmm1G7ZGs5SHcaMCfggU3gYzuKL5AdaSKktLprBhiqc3lIrspmhQZ2KwulrqFy9xhqHBonKamZp0rim7UZyFUzU5myUvlI0rHDqoIZzmR6IYzEuRGrs02wtbU2FU/qJX8sKJ8ETThnHi9Vw3v9+4IEPltQFN/9YJJjHwX/2iqX2AFte4aq/2GNtoVIgEgIKsnQuPHChj7vPHk56MQDjlkmQ+7YT8Za5R33y7a8G3vrzwOG5CW9dttQuo3B2keJr5NsK0jhGHfGW2kSams2g+XwMNTbgxo3FYSLoiHpXoy2KVhrPlW8FVbMUSgrnYjWcIeF0wU91v3+fUrywpdYRzvJ8wVuIZ/VFcdezDQ1q8rq+OCiIjFE464YGYSLhdNbJ7U5caotyKI8jkkYZK28sgdSZT0X3llrSflHAK5ykoey43gn6q9/+0D66yCCSkHDKkfOtIJxR6Tnmb+a7ogkKp7N2P+46c+0Od27EjeKs//5crX0XWanuuIQxNZyKBKQQ0CLyx6CDHCnVsdTq8vWLIjRo3yqcvVgCnR10dB+DbPx2lFb45/LNRRK1JZwfVTea3+Mta6lVUJD+e9zXtmStTg0ntF/scQqnIirbt52lNqjhzBGNHDdFEr1OhKRjCecUhbMgnCbl/TIQOJlw1kVJ4YxNsXIMVcuadWZ/iB0xQNQLCKdb8Qp78oUX7/6DAeEsX4xZrvxEpSsyU1Qe3AxnrZAepgrfGv8//Fry882n1AZXzSRf/tojUDgPZtQydVFRON0gEq+/wulrpVwIx0YonDalVsR+9XStj7FDi21R1AK9F6eirsLp1HxZNzQoUBpahLHUOvXPWWqDlFpVw770Vy8G/urFyANFfdkWIMBoaNCO6EPDhFwkkTR99uZQOLWdFEZSQEOU6vf/y599GD/wB++fuok01+gIVRDO656AISX41LtfA/z1S4AP/8nEz0GiXmiQ6xE46f2fJd+Pl3d+BVcO7jbb9m0tqpbaHL0ksgTZTXoTu/A75vskZ6kdtb76wCX7t1hMTqm9av+j+IXOr+JTh+8rPV5uizLxI46Fr+GMxlhqa17PyyqcjtDICZbaugonRNR4aNBeqHCWLLXTXzdL4SQhjaXW1XBe/6m4Z+sJo+om4EOCurBjt1c4tR8DXD0j6dznNfQw9EriQ3tDbMsMMikrnNWaPdImhMgrnAGBJ61NsI2QSJLRGs6hAo51Y1x/wsw50t61uAYX/PfnxoQeUu8ouPvsId5625lwB0o/iQga0hBOSERQONaNKym1yRRL7SjhdAT4YJhjmCt0kwjo7EBCQ6oU+Zi56M6ZD+BnO6/A1Xe90Txw5jaksod71Enze7JlRBudI6cIiZRIolDhnO7UKGo4XWiQMG0DFRUJtUBgqQ0UThS2Z3ccNAS2kghJ17x/OoVw+j62Mh5RvC9VMOGsCTeIJfkhsHUSAOzK6uyT5NxBim0MkGwV8cwqmtKHEzB22gkKZ5QdmMEJLjRIlxTOOqFBWxhiS6TI0mYVuLLCuZ6kZSbsRGVLZNMttSr3PeG8LdXak8gmEmu1vgqnTw3dqBpOSyaiuCAATROuNtBwSm34mRchQESE33vH3bhwOIas12yL4oIawkTFafAWviMIDXL9WaULDaIg6EPXsC/lAyA7NBNzoUsptcuo/yVLbSxxHH30xRYAQxoJov72SUNDQACWcMrS2L8/VNjtT1+MSa3CSZZwdh75VDxx+Jt4xef8hXnCBMucsdRGgcI5/lz5wD27+NKfexM+fP/Fie/vJvTCBt+Nt9QmgErRS0xbFJdaChkjFhPuw7qyoIai5KN4ekBGJyT8ukC+JAgMNPtevOfcltpcIxYaImiL4gJt6vZSXbaGc5LCWfRvnKOGs+HQoFDhhMqK0KBZCue40CAXgAMNCIGtTmQUThkB3/M2fOjEF6ObjCOc5j23POEcVTiVJV8qLwjnFlKf/XDhMMOxSBXqKACCHCEYPkDIMeowpdaN7zIgnF7hJAxywiddd8xfiyKKIQUht+ezW5AMazh/7c0fLy9G+XOIzDipzdgiBaBtMNeVPbPfhcIZTVY4tSoRTiLy38vBUGGQafQSCXSMCLODAQbj7L42iOn4g+82v5/5KM5vPQrD3B6zpGdEG51D2bYosZS4qOopnESm7ZVXOKMIShMypUv1wkK60KDiWOXh4qAnocay3bEK53TCWU2pnbqrlwSYcNaEG4RjdQj0Tpr/1wwNOrc/xA4G6GwXhFN7S21IOIMbzf6DE2s4ZWZitnXnhLXUArEek3Y7AYNUFc2zZ6wAzYvwJrWpKbXu+G3PaIui0sKuVtRwlu03tM7qW3XCsgEKZ+4UThkVgSWbUMPZcB9OlYeEc/7v6tTFAX7sjz+Ev/jHB0b/6BXO6dcvaUM6ak82j8hSq3RhqRWRtdQG76+0ublPTRbVCsgHyHVoqXUptQ0pnJHEDgY4gFmcSiKjUtYnnGQnhQKRNJOdcN+0ppmLfmmuEQeEUwiBJI5xqGYkQNvQICGmK5wP7Zn70m5//MKbeX+rqtiJsRhrqe3ApdQmIoeSha0vhhpv/3SEs6Rw2kl8dbENUxauHGEZE95X3W5duP7MIhq11NYODXKW6kUstVSk1FZrOKlyjCYiTKkVbSqcQ58GOzulNvguRGF3BeCVrO0kLgcn5nqqwnlFnJZ+B2l/vuf2PZTOoez5sSVS7Nt00t1+imNRViTUwqiXEuU6cjeG+zEG0qqg5BdChJDoJK73dBFSOMhhWqJYFGnHZadKF5l3tB0M87K9tiy32rmAgJTGUhtB4Zptc+yHrhXMrLYogUPBkc2tJEKqNPYG5lp2Pei3xWBscJCrP9059U7zwJmPYXf70cU2Y6dwKuSIrKVWYM+HBs221EaBwumCow5TVVI4hQgWCQKFEz40KFA4OxGknf9lw8mLy06kIJFACA4NYgRwN7Q4PygUTlHPUnv+4h4iQdjaOeEfU3HRQ8gjvLmf/wQwtKvClRtdkprH1c51RuFUClGphnO2wplYwknp9BqfeRFeNMsonB++/yK+83+9a3KRe5uo2Yfz4MAQ/5SCRs7uO3SW2jVW34S31G6OwpkppwzExlaLy7SGMziv6ioiIbLcXKdjr6+aKbVCu7RQWUu19KFBR9IWxdbmRZFZiQb8+Z2PqFxjQArIU2gdWmpdSm0ThHMfSSRwXPRxQOZe4FTK2ooVaaOICljrmyhdw0rTzDr6TBE6UKCoUNp6sUTfnV4TCKd0CqecTsJd4/NJhyzNNaQLeAqs3BqiUJQBb6ntJhIJFMgpnFE8uYYzaHniMBqIMzrpH92QqwUt34fDa2feuaJ29/SwhtOHUh1NaJA7LlHlczkeMlPhpJAkNatw7gUKp1BB254ZCmc001IbodeJcBgGJ+Z6NKEW8Arnp1xjz7W4IJzunuMUTspVqQXawYFZyL/Qz7At85LC6eoBw69N6/IiiyGlxnbrxncSEZJkTA2nBq47UWxf2HPKKZxu2z2knmT2s4oNvdpbMljMcjWcV285wumuvaR2DaebP5/cNq89s58aVbkbKJxj5os+Yff8R4GLDwC79+DisccCsNdfYmo43b0oiSSSSGK3bkotRi217vhEVUutKBPOPByrnT3WWmrduTNMp1tqNQQgR9vkXKpgwlkT7uKM80NfbF7XUru/twsA6O5c4R+jaIbC+eA/mJ87142sIsVW4aSd6xAJglZZiXDOUjz6mUJHmG2KvFnC2VRo0HvuPo+//shDOLO//OR8bgQD9DRL7cG++R72sO0VTlRDg9baUmsJwNiU2vUkyqkiq3DGXuHU66wiO/hFI9GMwqnDGs75CadbXR9vRRyjeI+DVlC2H2qdGs4i5OQICKdriyJjaE84baquKqy1kzeigXxQJEQGNZzLTAy8vTM9gBACx8QAF63CGdu0T9SduBOBrO0tltJ8zmDs10Qz216lubPUdvxjvSRCX7mEpPHjgCBlazjtBHnCsXSqxaTV+2Gu/XdVnG+6+M4cgj6ctWs4nTI5pS1K+DeasDjoyEWkJyucdVOP/fPtmCUCoi/lfJZa6a+nBWs4bVlO9XPVbosSWJ9JiOau63e9Gtfe8Tr/q1ApchHPVDcBIBobGhRY+YXEViIxCBVOpUd7cAKeNDzxGksqSzWcLjDNWmp1Dh0Qzv6hmRtc6OfYkvmIwhmhXDNcqLKFpda1ylBBX9qOCw3yY7SxviYVcgQU7iofGiQyv0jyuIvvwL+i1xavGSGcoaU2QiQUrrZT1rLCOWmRhkqE0wUGXbFl9v/swbCkcHrC+aHXAu/4teC4BNt//2sAEPaOPcZsUxWEE2TKOyIpEEuBvorM/tVROAX5Y+bOg8EYwlntw6nC0CBvsZbY6kReDc/SKfNXG7zmFiDYUsvwcINDlBeW2gj1+rkd7l0AYHoOOehxhNNdXNvXAA980Pz/ipuMOhIMTnFuVm3o2PUAAJH151M400LhFA0rnKFLYxmF0x3XmUl5bcB+Dx1Kp6bUHlqFc5+2CnsEKWgSEHbAqdvEeyWYllK7pqphrjQSp3D6ye56qrEluIWHzrHGU2oXUXhdXdB4K2LN0CDKoREBQZPyaXAugFoBQ0vAKJxk7JYuiAfw17VXOKftBilAmZZTbgXcqSvLKOo+wMZOhI7Lgbd/xXNbarVPipXWUhsm6GqimcFtjnCG4TW9JMKhVzjHv97XcM4IDTq0E/tJhCxV2ofXjCicIaSr4TSptC7kqEipHd2+a8oenm+jbVFCC/LkzwqMUThVYcWc1w7nr9+ghtP1Ya1dw+nbDM0//ungRl1VOKlCyqdsxPyUwtjqm0o2f89v4tH3FmFVQhuFc1b9JlANDSrXXEsoCNcWJZibDDONThxVN+VJw+OuNH/r66JtEemAdMA4TsK8hr5VOC/2M/REVq7hlI5gBMd3gsKpCSD3XQmJbif27wcYZ4GGRBSkKYlKT16fuh+0Rfns/ZvxQvxF8f4VwknB2EJCIobGlZYzF4QzmtIWpVzDWVU4zzmF09Zwbouh+U7e9zvAe36r2E64mPre3wEAHJ4IFM64B+QDCFveAQBxJJFrgDo7NQgnmeuoYqntZ6p0vgkZI3ak0N07ERU2ctcz1dZwunNHZZPv9cI6VIQQxmJ9GTBOJpw1oezEI1L9uRXOw31DON1qDgBot+JVDQ0SEXD8YcDpW81jJx9R/M0iCRROs40+YgoI54wbUD9T6El7E21Y4dREfpxfhnC649p0im4t2IE6QYbDwWSFcnBQKJxxYKnNIYtEO5WvrVWi6EE3RuFcY0ttIjQg46Jv3Rrblj3cjbl7vBGFUwc3elpA4XTX13iFs15okNA5lJjDUntECqfSMHWB0qgiblLoV6GdglOjhtOFqxiF09lHF782fH1idgBojePoY5+cwmkm7vVDicirEC6lVlQstZmaPpFJlUYicqCkcEocZtMVTulSaiu2xSrcxH4SeUnzkHAWNsGxCqfK0UskOkHNKaIE8YSWJr62O/ieR9W7MZP+ke2Yx0cVTvJhM/POFZUaU8MpXeJpTcK5ROpzSK5LcwcEoUEzazidjTC2qaoNXdfpQWmMFDpDLuKZCbWAWYMcVTjt9+cUzk7sF0IAG1w1VuE018RjrzDXwoWhI7AUtISyCqdSpbT0waEhnLuHKXoo13BCTA4NEmMUTh9mFdRwZk69tIszcVQOuDH7lPvnACZt1+VqRGpQXvgbY6klF2RmQ4Ou6pp9HOiifnqqpVaGhNNs/+SW2f+DVFUUzj76qQIdni1dh76vebwF7N4FCInBCaNwDkuW2szci4BC7e3sADP6CZs+nOTdK4ldQOqnClE0qnDqQOHMKYJ3o/gaTqdwmvEpn6JwCtImA0FGEOAaTkaAXBG2bAuMkHDWOUmGh7YWMyCcQiZm5b3aFkXGwLHrisneiZvMz2D1rGMVThy3Cmc+mFvh7AmrcLZgqd2xq3DLhAZ5hXMVShsVg2g67E982qBvvodDsW0Gb63t6rz0E4kE+dqGJ/kaznEptWuqGmbKJpDKGOT7cK7nvpbQOOEMrJML2J/divO4KPq6CqdTuVBzslnUcLascGpCbM+ROBKFwulrOK06MY0l2BpOZ6lFSDibqOEEgOwAO+hj31lqIzlf+IpdIZfC9OGsptQ68Xrawp9ROBUQF0pbN44wUDb0Y6KlVpcttZMIp1M4axBOt+9iEuHUGbqxUTTdtW+Uh3y8wumJhh5RNqttUYApC1duOyM1nArd2KlJ8yqczlIbtEWJLeGsuaDhrqNFlMUwaC2i8ucuSPmsjRRWT6rpcqiF9MAnFgOWcCKe2YMTMAsvniiHiyGOHIsIW0lUuiaGmRpfw2nPsUdYY9o5t0thDacoFMcwIDAd7CNTGgepQgdZpYbTkskSx3Ok0taJwzyHqLCVChn5lNo0K0IKXf/JYvP2PJoSGhTrQbHQ445R+P/AUks2NOhK+xEGXuGsX8OZ6bLCCRgnRWip7WcKF88+iFMXDoLNmH1Pb/gc88DJRyHumPEytNQKUtCiUDgBgJKd2TWcFIzvqIYGBaqxbYsS9uFUpRpOq3CSKCmc+VSFU0EL6RcgLgO+yYSzLjQRtmEnikFblDoyeGb9/M4+AJiVlCE6ozWcMgKsVRZCAiduMP8PFA1HOMXxh5mf+QAxZX5iVactSs+2DYjyyYRqESgibHfMxduEwrkKS214A1fp5OOTWsI5jOxCgs5BNi3NWWpjqLUlnL4tSmWVbuT/a4RC4YwgROXGus5QKQABdLYbsdTSkm1R1DSFc1xq8Rj4m7xrUj7zjmnLEo4qNEhGVuEslA6ti/j5qSRB576GU0JDBJbaZWYGpUl5agmn7RkX+9CgmteeCw2CaQehK+qo+3zTxuHMtkVx4xVgFM5BpqYqGALmuxcz6g4PZ9RwprkyNdlASVkfIZwyAVRmQoNEWeGMBI0NZ3P75KyJ4fftRbAwUGjSdTRF4ex5hXOxGk5ZquG09++ajoWizdACNZzBsYgrRNon+c4aV5zCKuq3RqqF9ABSDXG8a3tv6gx5TUttKTTIhTBZAmV3FlsdiX6m/KLDLIWzS2a8PuOmAqT8AosWhSqtA5Kc9Q9w0bYk6iCt1HBGkKKscPpzzyW7Cglpe8P6BS4hfZKxDxIiBYIoJ6pWFE637Z5Ikdm5SEcPZyicxWIW2dCgE1bhHOqghhM0fmGyQjiVt9QW40w3LltqDwY5utn50rXsPmf2iKebB675ZE8KU6VtSu2gWPxEEfxjCOfsGs5yaFBRwxmWcDrCWQ4NMsqkWRUYX8NZz1Lr7NOXPuNkwlkTuSbsCEsO57TU5gO7yhIonJEUSJGMIZxxQTi3rykGqgrhzBBDbl8JwNRwJpRiCBtUU4Nwdq3CORfhPDwHvOwJwH3vmfgUpQrCuQzRetjZd+Ct3X9XHLujRKgSpP3JdrCBGcyy2C4k6BzQuVU4bSN1aAxn1FGtCkUN0CYpnNrbJZ1lZxGF78ihUqPS2BvksihZahdQOIrQoGkK5/TtCp1DiwhUCeeY+PzSpKa9m6tyoUEyRizLCmdoE5xuqdWG+OSZsQsHCmcjNZwAMNzHdqhwjiGN0yDCtijCfs6ArLoJzNj+dhauhjMMr+klkRm7pxFO0qZub0Zv0r5VYiapZakq2qII7dqiTLLUZuglkVFkXRsXq+aobLSWLFQ4TSuc0e++dE5O+qz2+44xGhrUS6zCOefp7K7f8LhHTu2sueCwTEptqHCOEE67udp9OKVzOTSwsKo1kB4g0imuPmYm7dIpnAuHBmm/r0JKbHdiKE1e7Uvz6YQTmXGBPXhY1Os5V40jnDrPKgrnAS5YwhnrdEThdOdk8bGLelggrOGkomWKlL5Xq1fjtYamssLpSKmrfyzVcNrPnFiF05f7VAknbI9fYWpOIyicjM1zDr2ldkrrpEofThcaFCqc3YrC+e7b70UPWWmMdHPZ/KanAxDAtU/wpDDLyfbhPIS09yIAnnzrWoSTTEr2mBrOUOEcZ6n1pRoBCdWVlFqasrgsXDiacJbaqbt6SYAJZ00orbFTsdQmNdqiDHMFmdmTPiCccSSMwjliqQ0UzmPXF4NeYKntqgNj40zMREUqo3AOhRnUxAyyMEgVOlbhjNUchHPvFLB/Cjhz+8SnKCL0kghCLKdwXnF4F24SZ4DDswtvY1GIYADtibQUoR4it4QzTxzhzABSxmphB/0YOYZLpPW2iZG2KBugcObaqVdhDed67msJOkcuYpwdNpNSW7LULpJS20QNp00qrbYfmIRSnWdTASNjQARf5xvJIDRI55VJ3gxLLcyEQdqUWmcfXWbfS5PywzOIoEttUUiI+mSciklhJAU0iZLdV82jcMah8hCZhHEZTfyspoZzdmjQrJTaNNeF0hK0etBiDOHUjnDmPjHUEbaxdlhHOK2aFC4wFHX1AQmdcB05i2uVmIVEpQlLbaFe1V9wALAQ0QsXpUcstRX78ZSNmB/CWGobaXeUHQIgRHqIq491YbKXtanhnM03jaNhHOF0+wrpFwkGqXlsOKMtiiOc5wNLrfuOXFqyVqoUEJiHhJNGFc4RC6UeX8NpWmI6u23k63zdIiuRreEMCadTON1z7M8uipTaDg29ZdcfI78vpjxIwyxkwdZwnhTGqXdW75SPzzjCOaEtypUh4YwlEG+BILAtBnjPR8y8sqS8uvN051rgm14LPP17A4VTGUstacR64Aln4q7JZLuGpRYlS203qOGUFZuyXyQI2qL4zxqGBgUKZ5hcXIUg7R1Ckms4GSGURmGp7RwDRISO0DML688dpNgWw+J1FrGUGKBjmtY6kDKWimM2DOj49UH4THHi9tQ+DsUOZGcbgLPUphiKXrGdKTBtUcwgMRfhdNud0upDa0IkBbqxXM5Kau1Lelofo7YQHL8uJvfizIfmRlQonArQGjkkpLPUivW31BYKZ+WmYzGtNcxRQ+tCvUK1VmWdoVIcqgif2FXNEM7gJr8I4SxqOKcRzhkEknKQiGoTzpJVtEXCaeouA4XT1RxR2ZEyMzQIANTQtEUR0tdX6SX2vZQounfK/MAWYmnSCudK+/RtUYS31IpxCue0Gk5lajirltphZss7plhqSUhI3ypm/D7PttQGbVF8aNBkS20vlvb6d4TThbaMScsMLLVEZR7vSElJcZ5w3/RKaeVYpCWFc07CqUYttb7tTt22KA1ZahNUFU5nqZ3+magNhdMqUgmluGqn49P0M9RsiyLFaIsRrQr7rzQ1nEARaGUWDian1Lpe6SmCtijKhQbZBQ+dl9pz6fQAu5ZwRmpYVjjHpNS6RY2QcEZe4Sysy4XC6dRLU8NZUn/9wkW5VVsPKVJrJe6SWUjzY2B4/pIGbIdKKYRXOK9Q5wAAp/RJ+zmckjrm2qMiiAcoWgi5tiiAreGUEki2sYMB6MCIC6W+uc7OHkXA478UOH69t8ymORnHEICu7heE0y4MqrimwmnDpICCrA4yPWJT9q1LRhTOsmW7ExWhkWrKXFlYOzT34WSMQGldWGo7x0w6nphdw3l2P8WOJ6plS+0QSbmey4cGjVE4Q9VNH+BQ7vz/7P15tG1JehcG/mLY+5xz3/xeDlWZWZOEVCUJSUYCWRKSRYPoZVZjwAZjEM1qA25jN6uxBF64m2YwbYwb2oyLNoNxA60GYSEtxGomA5IQFmigUGmgVKoqVamqMrNyzjfcd+85Z+8dEf1HxBfxRezY++xz38uqVOaLf9579527zx5jx+/7DR9EYDiV2aJ1HTrpAac7IDE8JyM7gNYeATij1G661YdxHnCuC2P+0SNMwKb/3ANOvuCb68Vp9n4y26sAOE0fJbVSU2jQsmCpz8eIkqwZhvOnnruLr/wj/xifee3hhktddBhHCaSH/WMPa/yP//yT+J3f/sEH24jp0EPj3OmH4uHkL/mLhNjM9tqzBQCYGL5CqxngnP/854rh9H04LSAKD6c10UsELAgNAgDOcC4E1nNDwKILShTcfwkAcObWcTFtIVOvzoMjMJwAk9TWGM7p/d0PPqWWM5xx7p6R1BLDGSWAUwxnPx8atDcWjaJFb1h0Wxv6kbIRmsyvIsPp9zcynJVevKRUiQv3rO9h+AxvmTJVuAnPgUa+ePSS2oul1NpKH84MIC0YlC5+Ee8kL9LpguGkYzkIOLmHE0eEXc2NwEg1rsfNkxZtAJyDaBaHBlFR6faWpRRHQCCj5ee88//fDam9Tb6xnOHsXWqLQkUnlzGcrBd6tw0eTucDkHhKLcZ9OB3bP8CzoJRcmoD9GHCS1zJnOKkQmwo4gO83OQw+qXYj9rmsdyI0SAj4wp2wuNx7QPiCuRK+KJyPBR5OuiYrnQB/lDG3l3GCHW4GBjUrApGcWCclwIp7OBt/XlfmnLVF8efC6JODgNNFD2cIDVJp26oAnGMP55jhbJvG2wxo3T7MAE54JYcIDOfnoyHD53o8ApwLR8Zwri4DUnuG8xDgPOtwIna+khGqMYA3Nu9cG6tnAMYezstPVBnOjT3FVl7ycgIAwuyhXY9eBkntgQXRrjfeBwOgOYbhjFX/GcBpHaQQWOsHA5zRFP8wFufHDjaBrtFNMpwu9DDtWGgQSWrBQoPetP2VqD/ZjIfzxXs+OOXl088D01wZ1iX2Kkpq32AP50+/cA8f+sydB9uIGTBA4czohy+pvYD8ebAW7xefgam9EG2+UJkaPDTIf/4Aw/m5BpxSJV8kAFiTeVZncbplgDM0Bie/4oOk1EpnsaP54vQFAMAZ1tGXdJyk1gUfpcd9o9CgsJn9Akmt1HmYx+6Ah1PCA07Jg1kq43xBSu1KFB5OVCS1UgOmw/ufvILrK+DmFa/uIYbQ1ABn7L/oF/fGOlzBOd4lXoosHgdJk/NI2E6D3ELTDy6l1B4JtgjwSZYOHNtILPZwEsN5/PPP5wxiEWksbYtChW0hVWiL8vAYztZ1uLLWOAm+wd4tZThlvEZ/8p/8LO1oKsKLJKmlYsh+mEipjYDTr5Ga1SpujyaPFBo0ZJJa153j7rb36gG4CsPpMkYr+sLpHhCChV0lD6cKzL6Lctkgfa304SzbogAeCG87gw06SJHY02nAKXD1ZI0nLmmcdK9hp67g3LC2KMCMpDZdL0pD10rgUgiDouuA1SVcEnvcQACcvAhEDKdMgDN5OC3Q+Hlgbc8i+KeU2iWAc8RwssJDCTg1rffp+eAMZ9jPNqQI0/pPuSRjLof3wSv/bnkUGvRo8DFkDOelUPU5DCZeP9t7uUBzkvUlUlJi50qG0/jPXH3Ks6iPvb/q4dzYc2zl5Qg4ldmhcR06uUnbmRnb3kQZTeuOWPwuAJw2MpxytrJ++LvChP75AJxcUiv6aUlpv0UPjUGFl4kdPIviVFwIaQxvWsAp2YIMQJXhpH3/vPRDrQwvqbWZpPaNDjgarHtwWbTp0DmNM6MeCsNpK0l+xwy5fQ1/v/39+JLb31/Z+LK2KNIZuCw06BDgHC8k3ohhrfftUR/OVInO5+vZlkvRPhAktVIlyWNYGPyFf/YJ/P9+4rNH7ZuExU4GRcSpZzhPcRIXN8dIav2CBb5xeOjDya9ZCg2akdQOY8CZM5z135XBv3vI13pIUrsfLBoZ/i+2RalIalULmB6bVuHWWmC99syG0BTOUZP1kaTWe+GsA/5P+u/ibzR/LO5PBtam7snYl3nIQFhvHsDDSYCTeTiTpHbh9YfL/jxuB9J3XFxSm1g5auPxwCMABC0srq4ELqkAOMXCtijCz9eDsbi9ZZ5g5uvcBIaT/MUHQ4NCYTn+m4UGOc4m8nVRf4675z1WxIoXfTglbM5o0b0fGU4JFUBpOs+6ynBayKqHs6ZUsf0W297gJOSRxETYCuBESMC+vFnhC26uIM9exnl7C9aFeyO+fyeePR4aFJQlWkpcXvn9I3WAaC/hitzjXWsP7GuAk44bQJFS68+rgmGSWr/fvQ5tUWaAXEypLdqiAGPACYTCQJhXejeW1K7alJ4N+Dlj29XnFUqprfVlfauOR4Bz4TDWMWlsYDgXsFe3z3rPjDL/JuCTtHrIvDpEktrVZeBbfwr4iv8oelX4ZHZiz7BVlyJjKs0ODXr0JKk9sGDZdiYGILT2GMBJnoBpmYCJHk71YOmslAI3Eyv9Rg3us/IM58Rx9Ft0YpUi+u0AERhOpVNK7Zt3IikAZ4XhpH3/fLSnqQ3uz0uhQW8sw2mte/CkYdOhh8LpoOEeAsOJB/Rwiu4+tLBY93ent73Ewyn1YqkpZ5MehCU8NAxjwRuVhwZxD+fscxn2TxqS1LJE1vB/3/nBZ/EPfuqFo/ZNwmJHEnxiON06RflDAEuZIpbmSn04edFoiaS2Dx5OyRiYdRP89zMeTpKhxVYeE9eTVC5Tr8lusGhlYDhZaFBVUuuMXzzaPr4XZfRwTiRlgklqrcM1nOGqOGeSWn5Pzns4W/TZPLgfLp5SS2wYB/pLpek0VJy/3eyiujb4nNFgyNi2pcFaXOr5sD2cAHC9sThRYXEPzev1k0OG0KD7+8EXYPyOphRYkQAPFZKnQ4PylFrya8K5uMYiwGkKhlMOW9zZ9rjWhHPCQ4O4PJN+VkhqfXKpZzhd9HCKeL9HwBuKM3lKbR6kxe9r1++w3XdYiZCRMclwunT+pPb35OlL2K5u+VNi7GGGUyaQSMU9rQQur/3vRd9sewXX1B6/6BY9r+N1iGKFGZK9xj6c9FGRM5yDOgHgchVhuZvUhzOcd1544G14YriXHeK5yj2cfj9XDQFOf+80GHDeT/ngfWiQEBJKuGMf4Z+X4xHgXDiMZX0420vBw+kOyk56Y3FJ7MeAUwkMTmWTVAScAHBy00/kqgI43Rn28nLUr+thixZDBJxLGE7ybazcbrlZOTIf0wt8zy48BIaTpUR+zsfC0CAxbP05J3M8MZyQsfL+ZpbUZp4bVrkDMGI4+zcLwxlbXnzuPJyDtdj1D2jqNz06p7ArfdsXHHzBeJG2KHYIcrhadXoxw2nz0KBDn2cLUvOGMpyJBVeFpJY/i7O39CilNnlVyb9lrDv6uRCOAc7g4byPTWI4hTqizUXZh1PkktoFKbXEcCrOcGoFYx2cmJPUGjiW3DsdGkRtUaYlta0geWtgMyj9OPtCFlBiurigIw+kqxRBZWQ4vaTWhsUlD0vh53pyHomS2iFjxTnDeWgdUI4UGsQYzmPmMyoEuov5iimkpkcTjqteiJk9rujhVHDi4Xo4AeB6a7FRaT+X9OHUITTo3pYDTpMSiKXClbW/Z053A6x1GKyrA0665wJgGSLgtBGoUbGZM5ydaCGHLe5uezy+Cecka4uiAsPJznmYR+idxpNLLZMuywDSHGMmRym1qriPuEd32GG/TaCe3gMl4BS86EPS+vsvYbt63J8SY1lK7QIPZ2Q4BS61JKklD+clfPnjGt/4jP933h+UAGeSnpPsdT9YlOm/QPJw9trLbedktdY5X3SqSGppOwDy4nY4V30EnCb+rB0BTuPbt1SGoDRuzp6+xccjwLlwmNCH00ntbyap0YghC6Go/p4LQJUFBgH+wRug8oAfSqnlo5TUWouN22KvE8O5Grz2fVCbtJ2ZsetNjEI/wX6xXLILvc7u3p9+gAfrzdarBw0NYh6qz/XgbWXWYjo0SA1bDHKdGE6T2qJQlbERb15JrSgn9ozhDJJmR4DzzXEMnOGMC7Q3mOGkx+OBZMW2R+c09mghht3RjMR4e5zhvADgNDOAkxYfB0OAhuw6HOzDydikN/LlyosSNM/6/StSaueeS5K4MUltlI/aBDi7I58LCYtBrvx5CwznfbeJPd98+MpShhNxUU3hSPx3CSzMMpzDAC1s5iWMrN0cw+moDydbdFXGkpTahhjOyKy7eh9OwL8HzRD/XbI52WB9OKktihI2S4TM5KiTgJMYznwu741nxrzt9lgPZ0gwbTjD6c/loutP/Qnp3j6ygEOsWS99MA9nbjPAeQTD+TAltQBwtTHYyLS4X9SHM4QG3dv1sRjD25gIIXE1AM57uz7O6fMptSXDmTx7EXDaBDj38hKk8YDz1ooAZ2LiSEKZ3TIs5ZR/xjoXiwOQKjJ98dxHD+cYcKZeneze6LfotgnUm5qaxfnnIzGcym/j/svYrx7zmzEuzfsL2qJQYa5REldGDOcltOYcze51AICqhAZxSW0MDWIeTgC+QIaUUtvTerg7He8f/Y7L26LwwgOXcFMQEweXWR/OcH+toofT3xetGCbXDR5Yi1TIfAQ4Hw0ag3U4wR6uueQnBanR4HBbFGsdLtcAp5L+ZZFJak2qqtGIgDMsDLtTSDjs9WVASuzRRMBJDKeYWSj2xqI31veGAnAi9pOm5nK8fNe/DF66Pd3byDhfbV83arrh+P4+8C/+bOYjGQ1iGD5PKbXk+5oLDdJ2h0GtM2lJlNRKCSfUcobTDMAP/umDJveHOUTxksleTG9ShtM4MEktnfc3dt9M2P6D+Djt0KGDxt6NQ8AuMnih6lAq9dzvy9p+LGQ4VclwHpLgZt6cN1JSS4uIGsPJGMBZSW0A5KaDhIOUMkmHkYox/ZH3hCT5VnsJ2N4G4BlOqqYfE74iGMOZJLWcRfZ/zhX+htAnLk+pTUmZkx7OIil6qtiwPRQaZCxakRc4RI3hjGntxHDmktoawykY4KS2KBIWmrFLNb/Y1HZakTOBvXFolPTn/qKhQVWGc8H1jyyLzv69+PvDsfZi5dVRdnzf+L/PAc4A4qB88eEhS2qv6oExnAs9nFLAWod72z5J6Z1lLKGIgOd0l3pkL5LUSubhHKXUDqGoqDDoDbTZ4e55jxsrktQmhjO12OAgnzycieEUoU+mYz06I5iM7GVgOFVF/klrqEJS2+3SOXbMC8rncT+3JHkvdneB/gzdhgAnk9ROtSRizzDdR3loUEqpRXcGnHvAmT2TDGzTaDJJbS5Vpu8AgF4uYThD4V2MAWfZFgUI52smpXYd2FsIASu9emBq7UShe9G3+waHH74ZxiPAuXBY5z2cjoBjCA06FBZgLHAidhCrsYdzgKxIakuGkx7q8ELd3QMAdEGWtUeL9eB/FhnOmYXitje+Yh+qkRvsFy+kY8XsUB9OAay1nE5H/MT3Af/kDwEvf3jmy8I+mc8Dw+kGbBHiticktc45NHYHqzfpGkVJra/GOqk94FyyGPnsh4B/+l8DH/tHD/FI5ke2QLAmZynsmxNw8j6cyc8yHWL1MAYV//cPIBF3Q4fead8KCXjwpFq+iLiIpJYWvHOS2pntOueCrFJfCHDaIxmZY4ZjHk6t8rYoixlOWgCytiixDydjOI99LqSzfmEULBYOAudYxcWNwzEptVxSG9hOx++Lw6FBllKKFU+pDYvasiDKjyOm1Ib9rhQ5e2Pj+Z6T1GqS1BKrjIqH88QvdHH3udzDqWcYTvLhEsNpk6Q2ejgX9OHMQoPYcXSDRaN8r8Kjp0diOCsezrmCcdpXYlmO833SoOdvkCt/XGwNsFRSS9fcPVSGMxWzr2iLk8Bwdk4vktQqQQznkApNTAILoXDS+nZJ97Y99gFw1UOD8pRaIxK4d4Wk1iuEBgzQsGqDNTq8eG+Hmy0BTi79lJClHYvAO6kopIz3LV0rKSW0Yoxq+F4bCtxxtxUDwcgVWzA79AxwJuDqUl5IAFCOzrfUsWdwt2GSWpZdMRplH04CnFJGwMkZTnT3gfNX/f6X6xIg21bLGU7GHBP4j306I8M5DThdbKFFktp0j2WpyLEYNO/hXLdJKWKl7yM7nVIbUsYP+ODfSuNtDzh/81/+Yfx/f/jTBz83GIcTsQOaADhVA418AVMbJgDVkuH0Eqgxw+mmJLW0MNx7cNnrKwCADi3WhiS1hz2cO9aDEwiS2oWA08Vmw/NtUUhSOwlkCbDOsTyxD96DMUEXGcJZ7ISfrK41Q2zgzMd5Z7DGHk4XDKcdvKRWCDjZhCj9BV8a2A7cf/khHcXhkXluSkmty6Vwb67QoCCBkQlIvLHf6S/gA7X5GXxoUAKcD1ZIyRnO419UMbTEzQHOOaWEB/5CyMWAMwtouQBIPu+GRf1gDStKKCmzRTm/jycX0+x8SkuSWs38iv73rLsA4KRqengf+EWRSJJaofI+dHOD+ayoD6fgTNUCSa3pK4CTeksKOc9wCskSMcfn8rzj4Lf+/d1g0VBblMhwVtqivOtr/J+f+sFsf2Ul4yDuo0t9OI1NHk6FlFqa3ZMT4VsESjlb4Zzz7OwFJbXEuMmsD6f34dbA+2iMfGTHMpxh0SxXkMKhZ+9ZXkSfLagbAkLBw/mQGc7LasBaMoZzgaRWEsOZSWoTaIPw7Y2urPUChjPvwxkZTmvSnMsYTmE6b5NqNthgjxfubnE9As68LQqXdftdTJLf8KF430ZwyRhOx4qC45TaXHbL51o57DBUASdjLJ0NYKgIDQIwRMDp2LpnysM5bovSKIErI4bzkr/uZx5wSsFCsA4ynAxwkoczzKWxawMrYox3M99+O9EWJSWUJzazZDgtBFomzXYHGE4JSvp+5OF824wPPXsbn3l92SImA45SoVnAXlnrgaoYhQZJ/7JgC8f7uz0+9PxpvqgqJbWB4ewbv72dWGFt/AO1xMPpW6Kk79wcIaklJknMMZyO+nDK6QV6bK8yLSEQ7jCb+kYN4Qbs0QIQeGzl8PztccrZ6W7ABnugOSk8nP4FoIRnONVShnN3x/8ZgkQ+FyNrCeBsLimLDKf/55ulLYoJzBpnON/o0CBiNR5EUutMjx4Pj+HMeqtd4PhJ0qfsTB/OmRfgYIMXjntpZ8PEXMaAmAsk6/5/fujT+Pf+/A8e/Fzq1eo9nIaCVcqU2qnFNJs/helCiqEYAeuLeTiDXDQCTj+PK8ZwLpfU5h7OsaQ23LczhZKYAs6sHNHDiZnQIEqhnAkN4u0ApubAvWEMJwOcI4bz+ruBK08BP/fP/b/Ds08MYT2p2u+TEjbarCRs1n9QIrVgmXqOUkptYjjpPmqV988dnUQeGc4m+7GFPIrhHDCz6J8b4fiH0LvbsDR4fq3mCuoZSAoS0AceDHBeUj020l/XHhpqwWrVP+9eUhs9iAwgivCcXV03hYdzTlIbGE4uqaXzHQseA2AHL3HWG2xEh944XG/C5xjDKYQKYDJ9FW8xA3h5qBTO13HivjMPp0lgcsrDSQUBfm+IYY9hzwCnqQNOrp7gc8Nw8oT/01jm4ZzIAaiFBik57sPZXvLzzPlr8TtH/lPBAWdgMIcccNJ+kqSWSIN5m1J+3oUQcfs5wxmOhUlqDW+LYv08otlN6lSDdpbhDPPcI0nt22c0Si6qUhvncMLTZmUDLex8BRDEcO6roUHGqQx0dfsOvZP48GdZqwIelgB4LT2Avrnqf0essAkMpyGGc6baue0N2gA0HAROsFu8kI7hLDNAkRjO9VxoEE1Qcw/Y51FSK52Pq0azwc21w/N3xoDz/r7HBh1EexIbLZOHc4CElIATetQsfHJs74QNP3yG87v+9XP48WfvjH6ep9Saam9HWny8mSS1yhlANdHD+bkDnA/AcJrOA04XFi0PyHCK0vt97P4Qw1KV1Ca51tTojYs+yeRBmWHSnIOAjYzMRVjZO+c97m77g2yStSkIQvHQoMLDOSmpZefz7OzMV9wDMxK/ABeU1AYpKr1HhpCk2DAP52K2ii0KRfBwCvBCBDGc09cxeh8V93CGxvFCTgNOktTOhAZRQi0wL6klhjOlylY8nEIA7/k64FP/IttfqclyMt7PJNENaZ8UJoU0Z0i4JJU8ADh5misPQbmQpDac1xrgXObhDIyTuyDDSR790EOatx9bynA6a2CdCMz/w5LUpoCXE5kYzs4t83BKWZfUUtsc8kgSw0lgoAo4ZfCnV0ODwrGGYrN1BsL2fq5pNliHPpdXI+DkDGeSy9IgT2gENtHDmdhZIeU4NCiE+9QYzvh7LKVWmB3MPhEaWUqt5PcST6llXsxLTwIIBejZtii5h5M8wo0UTFLLPJz+l7BtrvvvKQEnYziFEGiV9MU+3t80SmoDw7lAUosC6AOJ5awynHZIxZoKw8ll344ktVMeTjjYBb2M30rjEeBcCjgDwylWzMO5QFJrjZ1Jqc1f6M4ZGCfxHGfUZAE4SVIbGM4OLU4i4PQP2FyFdMsktX177ShJbfIEzPThdAQ4Z9qixFCSaWlurHZ/XtqihP52eoWbrcFzt7ejRe693YC16CDbzagPp42SWr04NOi1V71H4u4rzz30w/lj/+Aj+I4f+czo53lKrc0q/HStacHxppHUOt6Hk6q9b3RK7YMznNSH8+ExnCyl9gLgja6vmpPUzgDZwdiUFrwgZc8EhtM8AOCkBdqh58mye0Tz0CBnc0ntAobzzulpBK+0WKXFoXXHF2Jiz7fwPuh1yXAewRRxFgLEjqX9+U34h/gv1HfPS2qHcP054KRWH5gODaJzImdCg7b9GPyWoxsMdCGphXOxiXs23v11wD4UY6OHc5rhJACrgmfTOhd9xC6yqS7275sqsNDcvxJ9vGfondkoL6k9PjSIGM48JLC8htMbqCx6jxj0rNoAOIeOAU52KIfaonj7CI4Ku5odDBxo22ElSFKrFgFOHSS1p7s8NCgCi7C4v7puvIdzmJHUAv656DxAS35NlhwbnhtnDIQdMAgN0Z5gA79GuqrHDCe1ReH3jGDBQPQn3bcuAk4FrSWsE+ln1sCVfThDESMCTfYMq2EH2zHAyf36GcNZ9OEM+43NDQBBUqvmPJw2A4mc4bx1yZ8zak/D18bb9iYABjhjem9+fVotRwxnktQuZzhroUR0L1Q9nJmklp+v4KVlHlCoBo0YJhP+ffsnFcHsI0nt22A0Skz2yeFjMA4r9BA0cQQP50H2ynRohKmk1Ap/w7KHVdgBAxSevV2T1IbPhWqbC3HQnWixsUFSS32H5kKDOoNGhN5o7VWsRY99t0y2Ghf2B6RzSgqstMJ+MHU2guTBc0CBFgQz4PaNGtINfsGjN7jWGNzfD7hb+DhfPd1jgz306lKKzLYDEIoGSorAgg+LJLUvvOgBp7n38CW1Z/t6lS1b2BYptQQ+4wLrzcRwxoTMz5WHk6SJDwo49UPzcD5oaBAWhQbNAE6bWo/QIm6utyb55w7JF+cGLVqW+OYlS6lNoUF56Mu0hzPt2+np/QgSUyU6Ad+LpdQmD6cJmQAkxXJCRqB0aAi4jAl0RR/Ob8KH8O+qH50NDYp9jpmXMDKcM6FBCsazvrQoq+zzEkltZ+wIcMZ2AeV499exHfD7GxvCV94TBNxKD6ffIWI/7UGGUzKGkwoMNB+22s/1R7dFoYb2PDQICLLoJZLa8CxcMKWWrqsNqijLPJz8Ws2n1Ppel575Fw+tLUovSAWySwwndA4AJkYMDdoOWVsUw0AbUGM4KwUOwBc2whzJJbWxYMZCfITtfGBge+LtNgAuR8CZp9R6H3H6mlgAiQyniH046doK4b2aBpIxnDatN9IXAOD+zHQ/SbuHY4CTb2fk4aS5hX5++Qk0oUAyZCm1y9uiKCnwq778HfiO/+PX4h3Xwlo6A5y3wibTO8hAZn5QIKzbSdZLa+SC4dyKsP0ZD6eoAFr6/SykKvZaZ5LajOEcM81Q86FBfp7joUFv7DrmzTAeAU4ls0jwqWGcg0bq/wWpFiWQKhMe7sLDGcMssmRQHzjzLPeUlpJaahMSgG8n1/ElahdKasnDaVbXACDT9M8NYlVELQY7jME6KOEZTs8AVM5P9IjNeDjpmnw+QoNoYdyscUX5fXyu8HF+/OX72KDD1avX4Fjzcd9SJVRjlZfULmE4T+94w/xq93AltYOx2A+2ChizcBJrMhBAk9+bLjTIOb8A5B7OIxMaL/KdwHza5+GNDG9cSu0FXlRU2dZVhnPs/SlHbyyUsD6CXxwG/tYhYzgvAjgXM5yWezhZaNDSlNrMwxkAGZPUcrn5MYUYn+zrgqQ2AM7AcMaFyjFeOGezT1qRs2MSFmt0CyW1CXBSaNAc4CzbotQAFw8NmmY4fZsSIAE74SrheQDwxJcA4Z2V2qIQw1SR1DIA65z3w8V3JUnKYWHlPMNJ71OeUkvvtZYktUcCTnqHClVIaoXMU0WnRslwHtuH0+VrBjMpqZ3dSFTzxJTaifPwAx97JV/XTI3uDPdVuMbDPjKcnVOLUmopWOjutoN1rA9nASyubryHk2wS0wwnTx1NklpSOYgocR0gA8Op15ewEf65uhTWD7n0UyUwSduOfULD8ySUX4c4F/ssC6WgpAyy6wQUSw9n8laOvfjS5IDzKA/n5SdSIE/m4TwMOGnebZQnI77uC2+lz7K18S4AzoH5T0c9ecEYTiAl1RYezr1b+X2YYzjpeyopuLzVTHas8dnjKbXE9ucMZwsz3RaFJLU8kOgtPh4BTiUXNbU31qIRJr0gKBDmwOJHD+HhLtqiNMFblIG3UM3JwE1kOP0E5oKBnR6yWA0EYAPDOSup7Q1WAXDa9XW/6d0ywEmTU7VZPH3GutiHE5hYpEcP54ykNnht5OeB4RTk4dTr+MJ47nb+svzYi/dwIvZo15eYtNPLaizJjGSzSFLrnMP+9DUAwKa/81AZu/Ow2KxV2QQsBgpUcSbJazBmON8sHk5jUx9OfI4ktQS2H4jhtEFSS304H7C/LPdwXqgyOsdwRmnjvIeTkmCj1HRmP4x1EHAw0QtzfAGjDGyZGtbB+3ylRqOnGc5JGSRboNHCMfq5kMCVtW6xHYH23wM1GRdZNvwZGc4j+hlSrH7cbais2ChgsRb9rKS26uHUxHDWPZxRZSAU5Iz/KAOcE6fat0UpAGfB3MYhVUqrXeLhLCS18fyz/fUezqLVxMR2Wu7hJEmtFpBi+vgmB53Xou+2g5wEbfkHK4veo74/FBQD82YGLqnloUEz905kOOFbowCT+/67v+ND+Kv/4lOH96u7j7viavjyHVZBjdW5piS5qoMKN7fPWWiQMwxYJEktZzjbqUQi9lxYlRhOOn9xPWhNSKjX0KsTrIOk9pIkwMk8nBQaVEmppV0mSa3vH2viz4jhTD57nyarmc+yZB55EUrZfVpDgsk4uQTWWoCrDOjnl59Eq0OPS+Mw2xbFFoAzrB+y/aTBGM7dyrc/ckHqL5ydBJxxTUK9OMN+EkM5OJd6fE6MONdySW3Nw8nzIkZtUZwHxi5PCxZq3sMpHaXUhrn/AkF6P9/GI8CpRHwY5sZgHRpa6AJeLskaSE8NPYSbvdIWZYAqGE7fwzHzDBax7zYsVEWYwDqRJjJLlZ45hrNLDKdbXffHdizDOdcWxXmGc0WAs1ZdpwlqhimNC4LPS2jQ4Bdveo0TWWc4P/XS6/4vzSZWOc3gGU5Dnorg4Tzk7/nEK/dxYr0PV8LGePCHMc73c4DTZQsWPuHRtTbOYYXuTQM4nTFRLinVAWbiIQ26fg8SGiRCSu0gk1zsQQZndS/UFmWW4SQ50/R96z2coV0ISbhm5h0bFvv2ARhOs5DhTK1zdM5wupLhnNgAO7ckjYMQo3AHYfuJdNTp/SegFgEnSWojwynyMK/ZYdOiGvCtKag3YgjI2WA/z3BGD+dYUjtMeDiNcx4kCubhrNyD296fmxW6aUntELzAYIxkaIheHe8Jslr2HgbS/cwHgUuZSWrDftC7DDZ6OGOh1gyZsoa3RSktBhQadKykNhZbq4BzwbNBfTRxsTmQgIYLawbLAKex/poRwzY5nIsezkOtkbytg691bL3o1p3hDq74vw97rGJokFokqZURcHZFH84E2gAvqb2/H6LPmFj90YiAU8DxPpzhvAguqXUDjNBo1pfDvOFiym6eUktgMg/t8/8X7vvAGFvnWMKujBaBuBZzZsxwxqIegdL0bGi7h8gAJ5vrM0mthSWELxLgjGAuCw1akFLLGM7RYGTMfv1Y2H4hqS1GoyT2EXCG7BKS1Epqm+JSj8+pUZHURg9nJqlN75Cqf5q6E/DroBdIallblEcM59tgaLksNCg2nGcMpy4aQVe3b8LDPWqLEhhO7uEMCafb3uDV+0VlPTzUrt9i7xpo0tJLBjiDr3NOkrPjbVE21/3v7WceSD5IBjQjhTXWT/oUPFFjhT77ugdXt8/G6a806Bg+HwyndNZX2PUa2u5wZaUzwGmswwuvBsDZXkqLHuNDgwykl98tDA36kZ97Hddw5iPVgYfaGuX+PsTKT0hqexarnwHO8Peb9z6Cf7P6HTg5/+xD26cHGdzkL3hU+Rs46GXJQ4Neu78/apEprAecJydhHnhAwJmpGC7wooqAE7Xq9OHQoNiHU+nYINzOzKMmyEnJL3cRGXQMsDoAsHloUKtkqkRbe3RK7VUVFlM8pdb5dPK/1vxx/F58+xH7nxYZVIB0rV9cE+A8LnwlZzgdC5whNm+NDrs5FpaKfllKLTEEOcP54t0dPvriaWppo3hoUAVwdhZfLJ7Fh1e/HdfPPlX9+o61RaE2TYLa0NTGe78x7GRgwWYWvbwPp3XOpxcHiSapIrysrUj+/Cd/EPgbvz5uh561lRjQD3kBL6XUHgs46RxWJLWfgz6cEaBqSqnlfTgtfmD1bfjN6vtn03edNb6NjxDpPqzsR28sBuvyc/ST/zPwp79szEx3Z3hxCMX5YRcT9fdYBjgJJNw57xngZKAtJMpf3fjz/lpYZ00znOH+Uk3G5ke1Vzh/zhoo22MQGmp1Ai0sGhhsHFmg8j6ccuThDACWviPKbtNcKWMImmBFRl/g1jVJbczBCGolKDR2DzGktUzm4VRJMiz43BIltU9GhrLPAGflfq20RVFSpDmUD1ob6zVMCMOMoUhuQlKrKpJalUtqB2NTj8+JEZ+1GuDMWOOah5NLasfAX6g2hAZNVjb9fB9T3h8xnG/50Wi5qJdaYjjDQ6mOlNSOUmp95V04k5gEpld/rgwOCtIn222xR5N6ETHASdXKQ5LaVgTgGBLH7GyfojSoSlhtFk+fcQ5KIjKcNVbo9NxPwqdzgJMm2QWAszcW/9MP/txDY+F81dt7OEW/w9M3Ntn1+PRrZ1AEGJpNZNqs6f0ESRVBtUxS+6M/9zpuyHO8vnrG/+Ahtkah1gS1KpuEzRhOyyqhNPld2r6IRhic7D53/UHnhmBSNGqa/kZ7OG0BOF+4u8XX/LHvxQ994rXF25C2Rw+FS5dCsNdDbItyEbaQFuizKbWzoUE2tUVhPqbJr3sIKbX0HC1JqfU+XwWtcklt1odzUlKbjuOxNS9wJL+icQ5PiVfxTry6rO0RkEJrZPJwUnVfs7YociF4EM5GsA94SS2BVfIrrkWPrpuer+P8KmsMZ862/el/8jH8zm//YAr0yEKDapLaAe8TL0ALi5P9K6P/t9b59jqM2fR/OjhMMJzv+hrgt/0j4Av+N/7fMTSoJqn1+0TSxCw0iP7P2ejNi4XaO58B7j6ftsMKABSuQ++aVssLSWrFBMN5bB/O2AvwWA8nPX+BeXPMwwk34B3iNt4lXp5/1oKaRwCzDCexiNm27j4HnL+Kss+26+7jpT7NkUlSq+tgpRi04L9z3jFJrWUeycRwAsCr9/1xz6bUAuBp3MRoAbmk1iujNEQo/G+ww3r3CnD5yUyyKQLgzFh/2p5MKbVihuGMYLLGrBUAhp6DTp1A2y7ligBJoVG0RXFBqhuPHRhLameevVFokLU5KOaD5sKTW3GOTW1RjpHUFoDTBoZzhlAp+58CLDSIfy1njYnhdPn9UAJ/oVu0mAacsUVWDA16xHC+5Ue7UFJrrIMWQ8ZwqgWhQc0k4BSph1aURwwRADxb+jgNMZw77NDGCWY4UlJ7ziS14sQDTrdfYOZn+ylnGc4QGhQm8F1v8Y8//CL+14+nBQfJuGIkf2XExcKMfJfGv/70bfw3f++n8cFP3T58DAC+84PP4s75NJCVzgRJ7QYY9njmxknGcH7spfvYiPCCbk5SUt3Q554D1fg+nDP3iHMOP/LJ13FdnOHu5S8AAJh7Lyw6jiXjLEhqa5NeJqm1Bo59xhYsl1twHT4nIzKcOr6cZvu5PoQRGc6wcHrp3h7GOnxmSQgGADgH6XxT8CuXHg7DmS0wL/KiChX6pgScfFtLGE6pjurDScWYOTZ0bhvA4QArD7aCh1NJxnTkxZ8loUE321QBj6FBzkbZboNhUegc7X8pqRUrYjgpnXJ5aJDgi0KQpJYAZwJXdsYvHAsXjGkjtqcvGM77+wEv3tvB0PtKSkjp2zTUGU6Da8IXM2tFIZKlqphSG/6s9eHk4z1flxbH0a82np9ia62wcDfsnDjrE9S5pDZed9Nn9wAHgAlwstAgKY5ui4Lgf+RABEA47uUezsRwHvn9dExBjmg58AvncoV+HnDa1AJsDnDugpc3817XilrOAd0Z7uGSvybDLibq751CTY1ZDloXWYcMcMZiGPNwAglwTqbUxvVeznCS/FEWgNNIHc/pYysLee854Noz+TalghIumy9dAYghk+zWMTBKRAXvw+kgioCbIBEvznEnN2jcHpK9eyZTamHrKbU0N2QptQsktcbF3x2NCDhvxm1GBtkZX/wvf4UznKTsG0lq7UEPZ1pP1DycUwxnKHxyO5L1DKdkgFMekNQq53udCi7XfYuPtz3gXCqpNTaFZAAAZLOI4WxsPaVWK8kW+8ncTTdxlugmdWI4hy12rokhE4Nk6We6xXCgQrrtDS6pEKYQAOfsA8kGySyrQSNhlKFB297g9/+dn8Jf+oFPpu2E37ezgPM4hhNY5rF76d4Ov++7fhL/6N+8OPmZ2B9Jr4Bhi2dubDJf7cdfOo19tjKG0/YBrKaJWothVpb03O0tbt+7h9btsb/+CwAA568/PPkqMZy1HpICNpNkcYYqgs/wMzdzrT6XI/YWyzycb2xlsGQ4qd3Dvd3CcxJeyJ3TuHbVAwz3ECW1F2J4o4dzqP7cb3gOcHrvnVRNBGJzfcSIcYuA8wL7vJjhtM7LM6X2Hn2qRFuTgdVphjPt2zWdJLWcObDOQQoXWmUsZDiDzNUxhjMBTt6Hc+n9bAvAqeJ9EX2s8EXKqRHVKkxSK6VAq2WQ1KZz0RmLXW9xtg3FNqk8u4c64DzvDW4GwFl7J9HzRB5O+lMWi9XZIdOCvxxpu55NcqwPJ6zxtjW4cUqt7bPt8dAVkp6WktqlLHfcph3SgpUNdyTDmRQqRzKctKAP4IjPR9SKbD3jvaV9sJCeoFnAcGbnKJ5rtt/DDsJZnLs1nF4Bwx5tKI73dpmkljNMXOZLcxNJwK9GhjNIag8ynMzCEQAGgNjz0jmfUmuFjgDo8ZXxTG4BOCOLxwHnqC0K9eoE83f6Po+WhQZVPZyFJ5Dup0F5wBltXmBz9qgtCk+pDft0+cm47swltTWG02QgbjA2B8V8hPPlGU6/fcM8nDWG04d9hvktsPSktJHSB3kNCzycqS1KJaW24ov1isRQxM/WTnWG04cG1Z8hCRM8nKQQOj5I7+fbeNsDzkYvTamteDjdAsBp6gxnDA0Ccm+kkLh5qR0n1VIVqd9ijxZNuLF7JqkVzfqgJGfXGVxS4UV/6WbY5jKmJk6y5SKVDeMcNAOcH/rMbbx6v8uqPNT02sy0PKGUWrUAcMbkwAXXkTylc0WGWN1rNkC/wzM3Nlkvzo+/fB/vvhI+3GziPVGT1DYHWPB/9anXcRV+UaavPY17boPd7QswnKcvAs//2OjHZ900w6lgE8vuTOYhiOAzXGs3F/D0ORyS9lHquHiYk3I+jEHXjxhOCkM53S383lAsGqBw/YovPPX7aTn5kiGciUDqQlKc6OEsGU52TDMM52A8oPFtUYqQitrXWQclXHw2HkRSezilNsg0g++SM+F8vp5kStmi+Yok6aOCpKbsSICuFcN8L87nfww4fSnuv4L1wSAEODfeixgXY0cznKWHM4ByLh8dpu+1WDxkgBMA1lqOGE6aQ147DduT2oOtCcC57Qxu6dA3unJv0DuBQCBnJKttUaoHsEBSKzxT5BOuwyLVDf4+ERZWEGgNx2BKwMnmxSCFp3Ox7u/gK+xHLiCpNen9z0bZ2mZylIDz6LYowTcb5IhZQTEs9leiO9CHM7A6QiRp9wzgrDKcfL9D4fsMK9/vPDCce6dhHPKWExODM0yR4bQmk6UCycOZGM6JpXC0UDVpHuEMJ/VRtQbK9T7xODKcBDjflW0yKUL4XBvODQF3ktRaLqnVKaU2JokT0GH7T+CoaJ1i1AqN66HMAobTOaCU1F55Mlq5DqbUjiS1rp5QC3hg2px4wBntSYmEcROSWpo/CHByebqmdocHPJzxPFYktTID8eGaMTl1yXC6guEUqsVKTDOcNM+RLcHNrKvfKuMR4JRiWWiQGXyfqWM9nDZ5/bKfFw3JgcCsSY13FZ7BHHDusUOd4RSqDY2jp49n2xucBMCpLwWGcyHgpP2s+r7CMIHhpAn8H3/YL7Z4NDQFNkQvUGXExcLMd8XdOqJ1B8nf5hatikBjeOk9c8NX4KgI8LGXTvEF18O105tYocIwQMDEJE4RWPC56vdr97soO7t07RZecddh7k2zr5PjB/808Le+ZfTj8xAaVIvmFnB5aFClt2PsF/d5CG+qjujhVJDqYoutY4cpGE5q93BvuxCEh0V9D40bgeHsdg8BcD4AeKNz1pShQRnDOb3d3gxQwkEovahxtaFqdGygffw+L+3DaYjJImmZSguDLKV2AcN5QtJ5IRlzYHwADUlq5+ad7/jNwL/8c/H7lHC+hcTNLwD0Bu7mFwJI8i3v4Vx6P5eSWhkLdcSmAoAcpud3VZHUAt7HeQhwejm1B7q1AK1tZ3BThu+uAU6S1Bb9MuUhSS0fkhbX04CTmCIuMxbW/0zApf6KtI+mz447YzhDajrt+zt/+q/gT+7+8NGSWuH6OsPJWOrZ8aBtUQpJrWOecvKXrtAfSKm1aQ0zx3CG+TLbVk1SG5go21z2QHjYoXEGPTR2g1kEOHmyqGEMZ5ybwv0y8nBOhgYlgoEDTpq/JEupVS5nOH/9L3C+2FMAzjiP8PctPQMEFoOk1jBJrZQqhAYxhjOE+1QZTkYQWEgYtcYaHTQHnJmHkyuGmKT2xvu8D/XKU7lctez3ycdIUjvj4QSAxz8APPkLU4utTFI7fk4albJXyEpGYBUIbQeNA5pLs+vb+GwzNnY1w3Dy0KChuL+sE/nvqCUeTpZS+ybpBPBGjkeAUy2T1MZ+mXRTSw3lDqfUCsbI8KGVyBb7QKjmCIVnbp7kklrVpD6cQ2A4Q6XJKM9w7oPM9hDDue0tLutcUiv6ZZLaBIwXeDgDw/mvP+N9lRnDSYm7Zt5HCQD6KIbz8HUkVmPuugkyc0fA6Se0525vMRiLT75yhvdeC9dOt1ChymntECL9AxOifErtHLjtjMV1+BftlRuP41Vcgzi7QGjQ/hTY3hn9ODKcw3gfytCgDDDEptFhsfAG97pcOuK9LTWU9LK/RY3SH2DQvULtJQhwLmc4E+C8dWWDvdPolvqmJ4ZnSChV8A2S1M4ByFAskrKJL+s5Sa2h+yj45cwDSGoPptRaxNAgIA/24DK2yUIQ27fWJsCZ8nHID2hm+6wB8IudUGHPfFo33wf8gRchHv8SAKxdwFEMZx4axAOHrINX5AAQw3SicpLUjgFnZ0vA6bcRAadQswzneW9wIwDO2jNaMpy+hRRSku+SoaZZFskktTa2RSGGM8iiuaQWTFLL7gEe4uSK0KD1/WexQjd779eGsCb2pOXDifmCcfrgA0pqCYy0BDhZG5gwX60xz3CCWJ0DHs7IcHJFAZ0vfl+EcJdLl68FO8veF3SgsevNspRa9pl1kwAUtWwidjF6OE87NCpnpvINptAgyY4xMZzMwwnj76XWA85ffuuO/78JSW0OOHMG1ktqnbcL0vpQeumscWVoUAF0qNDmEktohYJVa6xFl0gQvg8Z4DS5pPZLfw3wez8KNGs0AYwNhrVRqbZFcSMP56SkFgD+0+8HvvH3xOIgZzhrktqVluiChcqGNbBUOcM5GAvodjagL4UGpWeR5uIaiJ9KqbXWhHZ4bF9VM5tSq8I8JwsJ9Ft5PAKcWh4MoQCYpJCqobKBXBAaFCfU4uWS9Yez1OR2AITCMzc2eP7ONi2IGOAUw957OEnrHiS1e5C8SSWfSmVsO4ONDP8fUmplv4xtoclpluF0Pv6aovXp9GSLslC9mvdwHs9wLmnCTg//XOWWGvIiVFnfFRnOc3z69XN0xuKZqySbXcUixGRo0MxLe9+nYI0rNx7HK+46mu0FAOew89XUYuFzNsNw5oDTZIu2UQ+vN4mkNkupFYW86A0aZVuU4z2cwX8tG1zbNNijfWBJLYUQAfUXlbVuvm1LOI9tKanl25p5AVLgl9QpvXEuLZcq1lFSe5HQIFI8LkmpZX57xSS1xzKcsYUAS6mFc3lo0Nz7w6bnKio6eEBFjODnbVGWsmUFwwkJhLnfMIZzja7q4QYARc93KaltSFKbzgXNnbdPz+NxJMBZYzgHXAeB7WnASSBQwWCwXs53rKS21htaMubUhLYodE6cIQ+njf0VIyguGU4wYFB6OE9Dmu2xjL2b9nAuSSmm83lhhjPsryLlFSv+CrcQcMLCuDI0aPx5KtQdZjjDe/DqtVjsbTCgg8aut9OgkA0OEi5vwj3tbGTyaHF/OTCc295MBwYBGeCsSWqVUt7a4DzD6UQKDcKrH/d/TgFOPgfS/cNSaqVwsDYVgn3PY+EL2lS8CoCzllKbQKn3QTq1wgo9WrdHF4qV1g7pmkXA6f+dqQxCYSt2RzB2ttgDa8BbG/V2JjSIDbo+nOGsqR1aZoWzKng4GanTKIHeOr8+myE2kocz7Ws5J/v/Z0qKUbHHs9AWMg+2Ui0amGlJbSCYYpHhUVuUt/5opJivUNMoK8FSeenlIYazkoIFpD6cABJzCC8feNeNE/TG4aXTXfpOeqiHLXZoU/Sz8pPbHg20osloxsPZG2xCaBDaSxggZyVX2YiS2vr2faKa91oQwwkAT15d5VWesJ051oyCMxr3cD2cQ2RJZgAnhZvoNWAHXF0h9uL8+Eu+h+jTEXC20ErBOAFnB0iXglEEtUWZWfjvjcUt5Re1+tINnDa3cNK9dvA4xgcWqnhFGM1ZCA2q+cxUllIbjO9OwDqRKuBUDHmTpNRyhlNK+BfpGzxRl6FBUVJ7pIcTqsHVTYM9GgwPCDjhbOxpWT7vg7H4mj/2vfi7Pz4dPkXncV5SO+Ph7APgZJLauUU3hQQ5MQ2SDw1asB7ycBpLbVFIUpsq93wBfYjhtBBJjiUUyNOU2DE7K5mK26I+eGYacMbFmBBHtEUZS2oTw5nYvLXoqv2QAe7hzBnOlVboJiS1r9/3c4yIoUH1os+2N7ga1Bs11U1kOGO/TBelyseGBpXb5wFB9bYo6RpGSS2ddztk9zKX1JIqh85Fc//59DtHDGmH9Pzy/Z7pw7of0uKVGNWUdH8xSa0KDCc4w2nJwzmfUps8nEgL9qqktmJjiR7OdN5MYDivXb8RAOceGn1iOI9IqQWAK5uQb+FcCmSR6Xk7af25mwwMAjJFWx4alACnCRJX5QZ/L1EIzqsf83+WHs6oCBnbF2JfW0lFPJv8tvQz3hYl9OGss3EJlDqhYLWX1G6wx1aGfbQufvf3ffx23Bd/z1fCeqp9OKc8nEVo0IKCgaSU2liQqDOcjRLxWTAEONkcpmVgOBlZUxu19XkEnGLMGsNxhpMBxZDYrDioVu2kAibOT0LG8/SI4XwbjN/2/B/Cr+y+7/AHh8SsAABUEyqyCwHniOEct0WRQdbwrpt+Mnj29bAoZX04xbDL+nCSpLZDAyVJUjvDcPYGG0lV7RV2WGcm8tkRFk56gnU01uEEO/yKT/4JbDo/eZ20Cl/3BbfyKs8xktolDKcjhvMw8KAWOHOFgpRSGyaywffi/J4ffx6/9zt/AkoKPHkpTEa6haQAKNNBYojVeaEaaDHv8933Nvmc1tfRrR/D2p4vTg6Og85lwVafh7Yo+3LSC+csyrqDpNYLgxiIK7ycS8cnX7k/23rmwsOlRbsU/rwv8jw9wEgMp/+ebQDxiz2cEWi0uLLW2KOB6SaeuQ/+VeCTP3Bwk9IZDBPgbd8bfMv2O3D2/IenNxDmnAZD/iwsltQS4EztAmbbooSKtZMXXCCDFYsOFJactcFvT6mFCZhnDOfUcxn2bS/WQEeAUzIvaM5wzior7BAXh5GpYO+CVVlNF/MKFT4E8kANJ1IfTmN9ii7gmardxNyoqeBQYTj3VmT3w5ftfhzfor4Xt++Th9MzLm6C4TzvDK4EhrMGSLvIYiSG0/CF2JIhpS8MFIteH/KXAGfZFkXYJKl1UYJIDGeXS2rZ9SCvY2d8QrE8eyn87nGAU7jk9edjzsP5e77zJ/Bf/u2fAJAYoIsynARi1CpIatm7WHJJ7axKwoMBIZDWNzOS2ux5q6TU3r3r1wy3btyMDKd2AzqnsR/sMg8nZzjXyXIQU2DZs0c+zsnAICA9F0VoUATsSkVPpcbg76XIcH7Ut1Y7uZltMgHXeUmt/znbd5UAJ/VvF0HlkIEjnqgKznCusUKPDTrsA+B0jLHb21Q0ELApdIkNGWS9g3HpmteIg9LDaV3MHZkdrKc5gGBRGj8nvA8nMZy5pDbsY5BmT7YNigznODSoCuJZaFDv0s+cDUwzvw6qmVTAOBcKYUJm7Xbe6uNtDzg/cPpDeK/9zMHPubISLLU3Yx8EnOHBLRK6fAPf/IEl39G7gmcw+jgzwLn3DCdJasPDtndNNJRzCVA5emOxEuH/9Qo7sYJaynBSJXrihWicw5eLn8NXvPC3cfKvfFDG13/hLVxa6SrDOZd8SouQUZ/AyqAF6BKGs48ezunPKFrI0Ytj2OOb3v84bpy0+Pe/6ml8+2//GqyQQLsKwMdZk0lqRZhw5u6RzljclGFRtr4Gc/KE//v9I2W1xHAWBvnIcBqbSywrHiBnfbiArQDOqk9jZvymv/zD+PPf97PHHcOCwVNqlQxyvjea4YwptUFS2x/r4WQM57rB3jWwUzL2//VPAh/69oOb9ICTEhLzm3nYn+P3NN+F973y/ZO/TyxGiz7vI7mQ4YwLAp1Sau0cyxO+gxjOi7RFsVGdMP9iFqwoAQBKJ8CZ9eGceiypb51YAYa3AEkLsgg4hZlnOJmk1kZpXIXhLCS1s3LouJ9jDyfNmzFVHQFw9vXzHS0L8rCH83+7/8f4Nv1duHMWiiXE1EBUWbltZ3DJekVIrcCwjwxnKC7CwBiXGqIvHAZq1Bs6ekEBCPgCgXMOUiQW03/GxZTaBDjL0CB27ojhHCyeFK8n+fOR97NnOOseTjFx7V+8u8OLd/25p3up55aIYwbZY4LfMJPU8tCgufVNADJCiHmGc1ZSmz7/+m0POJ+4dTMCBY1kHVgkqRWc4VzH76BimGSgh3yc8wxnaosSv9+ld2lkOElSyxnO3V3g+rsyuabfVkWZUvThFKyIR1JvChSyQoH3g3SQRaJqzjx6hlMCeoW16LAWe/TqJHxt3ZMonBvvdxiagjal9EBtQUrtYGzyqc8MCgIkuXHWD5SNhvXhTAxnApybRvm1j1oBcJMKhBohFNui8P2lfZjtwylHoUENBnT9+LtNaKsFkawab7RS680w3vaA0wqdghNmxig+Xjb+ZXXgJqHqUjkaJVPKFZPUQio8fWMDJQV+7tUARFSTWqeYXQgICr3vCHCi8QtwMe8B6Y1DIwwodXEn1llfptlBDGfp+6L/toAKYFb92F/Hr/3iNb7l3343GiVzD1FFTlOOGCSx4NpQFXaJNJoWh2Zm0epTErV/6QFAv8X/9Vd9Cb7/v/xl+KO/7svx9b/gseRpVG0sHjjTRfkK4AEnJc1NjX1vcUOeAetr3id25Un/H8cCzgMMp3OlpClUyFmPQs5w0v9fRFJ7th/w8uk+tpF5mIP34RQCn1MPJ7FE5xf0cEIRw9nCTvVGNP1syAENARMleeWLitjHuRcYnUclXJ4WXVkEVXczhgYlb9OcJIgYziUBQ5PbWNiHM6a8RoYzLco5OJxcTId5qeM9jnkfTpcCaGY9nNaCL3ZsOGccTGkp8B981dP42i+8Fb5HhrTW2UP0HwUKhlPGeTOT1KLDbkpSGz2cFUmtDWFAtLh2PW7iHu6d+aKWZICzCjT2PU5s6IFXYQDL0CCaKwXsqEA7NwzUiGHkx0+SWmNTkJJnjvxnnEwqDwA4Pd8m+TPbP38YwcNpLJ4Gsz7MPGu9sbi/z/dPuAEWFUntTMHYhLAqv/9jkHDMoLmhWc17OGcVXM7BIHg4WWJnOXZhvsxDg2oM5x0AwDsefywynMr1EXCqIxjOk1ZBqxwQ+INL9xUxnJMJtQAjGBo2j9gE2APDKZyBpnUD70hQ+Df9LpBPkd1XRahRnGsMa+lC7B+p2CotPfy+EsOZCjpWKKDZBElth0FToSEBTp66KmZUBq2Saa0lmwnAacYM54KCATHQJoJlM9kWhVRbg6TQoDSHPR16p8frN6Wmq0hqV9QWRYwZTuH4+co9vSMvbcAKtkKskJwfUubM+Vt8vO0BpxE6sSYzI/ZMksnDCaAax57/Yh1wZn04g2eE5D0rrfC+xy7hZ148Td9JjMKwCym1OcPZoYESYtJPQ6M3FmvRx4ehuwDgVEiLED6MS1V10Z/hz37Bv8Iv/8CTWOk8CVhEhvNwW5RmAtxm33tMSm2YvOdAoG/OLr0cBhj5Iv3PAijQHnD2UIAxvg1KrFLqRQznNXEOrK8DANpr7/THcvfIXpwHGE6gOD9x0mSLLS6pZXIcYMF9zsYLd/39tMgbfeSIxRSpoSg06A2sDPrwHf/3yHCGBdT9/WGFA4BULFKNZ45EMw0qbb8ooMkvIuqS2oE1zZ4c3JvXsX1h59LMPJ8m7KPSmvWVm77eVJiLPQ8vklK70MMJVpQAAK11lF3mDOd8aFAnOOAUSTrsfHsVdcjDWcgGI8Op0uJGCIE/9Rv/LXz9Fz4WfiIh4Q6H0YF87nwRlxhOzvBtxDTDqV3wEhaL+XUjPcPJ9l9a3wpHhRRtOg430YpLdPe9tBmYTamNxQ8k5nixpBb+HV7OTz4tPb2vbCgSpJ6fqS2KIx9oTOTus3ccb1MjGMP5tHglfeHM/Pjnvvfj+FV/9p9nc4VvoVFhcWcKxsa6eO8TgIoM57FzYDi2pl3BOBGPC0Bki9fiMMPpoofzcEptznDSs5HO29npHQDAk48lhlO5IxnO8Jmr6yaTKkaGkwEL6sW5ambuNZkUbUkKmxQIWmkMkHDWesCpmrRuAGYBZzYHRkkteTi5pDYUTiicjdZ4FTlo9m+b3uEOCkKvsEaPDfYYtO8DbDNPIpeN5v5wPrKgTamnGU52rntjF0lqZVCjOJ5SW5PUhu4SzjkMJKnVqYDz7psn+Mxr53BEEE28b6NCoSKprbZFYZ78MuF/5KUlwNmPwW6S1Cbm/CJF2J9v420POG2Qxh4akeEh2n4uoYv/3oQGXZeAs/AYvP8dV/DRl+6F72KSWkOS2nCTakqpbaCUT6md83AOxlflQe1U5BqNXerhZMdaWRTHxQIAXH0G+JG/COzvZ/IHgAPO6YW1CsD1YQPORZJaVzCcNcBJUju1Cj1VFZztQ6oaBQotCA3qDa7hPrC5DgC4dOspAMDZ688fPJZ8fyYYzi691LLWNI4WLMkMT7IQixQaFKPVj2A4P3vHn68l1+PYIQoPp4F6Q9ui8GtXhgY5B9zvFgBxYolD+xwjV/V7CvDyenOY4ZTO+CbjwGiRRwzn3CKUnzPbc8DJgOhMijQFfknVJPnXzLwTX6ZRPrQ0iZVvIzy7B6TzvCgB+IAJ8lkt8nCSpJYznFIl/5ezsMZCCocW/bSHs1hUR8A5JxeVEkrYgywuwOwatNuM4eRz8XxKbZ/uIzbWjcLeiGz/6T15bXjVf/8BhnM13Ev/qHo4E/gDAB3kyd7DeYSkVqjRO5z7NWMfTlsPDYoeTmJEaVsu3z//ayk06GmZGM65d+7L9/Z49vUtfuK5O+zzU21RVFWeDPhCCz0D9DxR0elodoRkzFr7xFL2LpahFdnqkIfT+cAawQCnq6yHYluUmlec3Rfn9+/BQqBZXUoeTtuhI8C5IDSIFu9XNzrrvxsLqAwEXSFJ7SzDmTyckvtUY0qtL9AKO6BBkNRKGfMfRj04wZQBvKAXAacIn6HQIJfOUdhPL7ueA5xhvqPiP6wvgjcbrEQPJRxscxnhC1LxmXkSBdxkL9woqQVgpcL5rvK+qrRFWSSpXZpSq2RUbVEveilzwHm6H3Buw88mGU46h2NJrTzg4eSMsCeWphjO8XeTfxxCpnTdR5Lat/5wwvfTPOSZiQtuVvECMJLyjH5vguHUSqaKkh3SBBy2+4Enr+DZ17deikOSWmuhbBdCg8KEFB62zmloKbKkwtrojUOLIQLmXm7Q2mUMZ83Lwgf3DeEbvhXY3gb++HvxrT/8Dfh96m/GwJ54zmYltSTftQcfxAQ4Dy/SUh/OOUlt8A2QNKYmfxySL09GhtNXxmMYhNRoYGbBbWesT3IMDOe1W++EcQLb1x8Sw8mkXJxxJElkqpDbuIDwrCEBTao0LgBWu7vAn/pS/NK/9aX4mdX/AV//+t857hgWDN7XVso3vi0KX/hTaNA5Y4uij/Mf/lfA3/u2iY2EYlEEnC2E2QOf/pfAn/sq4Pz19FnbZ4mRUyNL1yzu5SiRnTkv/Fke+P3Nnkl66dfGEL5D6SZ5OGcYUVuEBl3Er7KU4Uytc/x3NUr6ZzKk1MbAtUlJbSjGlJJa5uEiyddsH85oHQjHHvdr5rUbPZwzB8gGX4w5oeoptTMeTk3N6oux0hI7mwNOFXzr7xT+fiWJn8PYd+icQ9vfZT8Yn6PIcBKDChsA5xFtUQAvTS3uJ2d5uxUP4K1LP4PlfThzD6cq3k8CDj35paOk1uEZBjjn3mW/+LW/i/+h+TP43o8km4SaOO9z729rXbxnXWwzxNIzjxhUHNJKo4fOGE46D2vMp9QipNQK1halVkgiRUg1nIxdt/35PR/UJWVkOKUbYjjLkj6cmjGcBN5gTQTogj17V2No0FxbFNaVQCWAEVlH6SW1BNKjf5LWDlWGkwAGK2QQA0t2HMHJiJyd9XNZAj61+cT7mjloUxBM6mvby+F7OcOZS2prUlaAetf7a3m/F/jhn31p/CFnUbZFUQtk8gQaYws+eHZ2tA86peUOgVEWRBAAeM8tz+C+Rq+2KYazcg7nGE5hTVXO7kKAVg44w7xS+W5qW+W4h3PppP/zeLztAaeVTaisHljE0GKKafqBw1LDKUmAJpACBMCZ+47e/44rAICPvXSaGM7AiuxcaotiNbVFaUOIyuHQIM9wBkmt3KBdzHByf9cBhvPdXwf86j8NfN3vwq69gS8XPxfPcTxnMwxn9tI94Gmjl+KSPpxRUjvz0VhhpyplleHs/DkUvumycTIeT0ziJIZzBtzue4sr7iz2RH3i+gnOscb+7O7k71QHsWIFw8kltfz80D5ZLqMJDKcHnFQcCIvBGTARx93ngXvP4+eufz0GKDy9e7ihQdY6aMEApwCsk29oSm0OOElSm87FvW0PvPYJ4Ef/MvDsv5rYCElq/TPn1ArK7IHv+2+B1z8B3H0u/+xChpMWyq44/oG+bwbUcUbIcMlP1ot1+r4lyZNSebuAqWGL+e0i8qHIcB6U1Oa+HN4uajAuMhrTDKfftxxwStb43UVwrYSbZoKjpDYwnFRwmwNT4ghJrbO57I318ORz8WpGUqvcACOXMZw63DPvIMBJAVAVN0dYCQABAABJREFUhnM/2NgSxe/rnKQ2FRd7Y/1+H+HhtEKNFBic4VTC+QUhsQoAhLWpD2csHhcMZwTCBn3wiQmb+nA+LZZ5ON91/hF8nfxp/NOPpIW5YJL4bMy0RRlsYr7pmb8owxnndaXQQSfABEBRaJDo5zMqQkCeFCkUsfb5XY3hpP3lEv7d/RhmU/NwLkqpDZ+5stY5IxmDd7iH85jQIF9YNk5kEl0RAKeyfs4meXYMDqownASEHZuDCWwkSW2yKcQWLATGDjGcgJ/vCKhSGmqT5jPRXgrbr0hE7XxoEE+IHZyEqRVIbeHhNDYGo80NYqVtLHTXQ4NoDu8Gi9ff8Y34/f3vwO7Wl8T/f3fo9PDKNtxzU2vNig+22odT5uASyPtwknUu+50AgF1l/RqLX0KwMKrltqWfr+NtDzid0CH44cCEHRlO6svkb7ZDctyp+HMPUsYMJ004H3jHVQDAR188DX04+wQ4maTWafJwamgpYcV8W5QIOAPbMqg1WrcMcGYs14QROjKcUgO/+LcDv/KP4N7Ju6GFGS0wloQG+e9aBjiPkdTamQWdgoWVSwBnMKtTe46wn7EiJxvfvHmGKeqMxWWXJLVPXFljhxb73ZFtUYY64DzfG1xe+XuWF1Vo8Rtba4SihylSaumaLwnWou/+gcu/CndwOQVtPaTBF5GUUjtM+Mce5nfSoIXTeWdilP7pbgD+5Z/z+zB1nwb2QOkAEPUa7+ifBT79g/7/6Tw55/8+0y6IhoIZ9w8Mwy5hOKcktVw+OPN8WmqLope1RYn/Jy+2QAZ4D9353y1DgxqVgrCMtbE6PjkHEMOpmBdLqhToESS1NEw/cd1LSS35ktQhwGln56f4UeSLQi+p9d/JAecGHXaVYpy1Dg1M8tWysW4kdoWHk4DYk8KnicZESTEGnNvO4BrSHFb1cBaKFwXj21/ApnO9YFgx9pFlxU8A1tmM9U29VH1SJEmuaT/8L9HcZ1PxIbz3emPxlHg1Hd/M/SzcgBV6/MyLp3j+jp8jlRuqLC5nqUfH6dJ8FCW1F2wzFAGTkJ7hZICTg3c7dW8DXjEACSkQr5ed8XCaGsMZntXBWKjhHCZ4C6FXQL+DtCw06BgP56YBWBujlFLLPZwhNGgWcCZFW8zIYCyXCCobFS02AaAuYDiz+bJg2qgo5RibSgqLuMarBCHRiK1T4O9fJ2TGcIoVMZwDSE7BPYljf3gaXFLbY6Lg63JZ/GBcnvo6MVJKLa0/6onVdM06YzHIFf6m+RXQLKWWAOfLZ+HcTbybBV2DiqQ2u98ol8OZWFQxLr0PYL06LGNFw/pRVtoOOpp7uFXjAjaTn2/jEeCUGhrmYG+3GLtOE1D0cM6zKz7cYyo0KPzc9HE7JFN65sYGJ61KgNMkwLlHE9uiQLWwToSUWs9YzUlqB+O8L1IR4NxgvRhwckntFMOZL/b83xu0THomC7lmbWSA8xDDGftwLmA4CWgdSKmFUABVBGstLIZ9BO0UAEXSiXi9aQKcOc6uN7hkk6T21qUWO7QYLgw4x6FB10/8vZoznHmF3Brf7ytKaullZY8BnP67Xzz3fpBjgoamxutnXZZOygsaMiwAyu/57/7hR/Ctf+tDD/zdQO4XTAynwTuu+Xtj9/pzwI//Tf+Bqfs0thAJLIleoeXeZGKP6TgWSGqFM6maXkpq4/aWSWrNhIdzTvZK3yEWptSWDOccOJ38zoUMZ5LUcsDpJbU+LdFXog95OEtJLfeq8uRB201cryKJM56DWYZThfTzZaFBZUotMZzE3gHTktrBOjRigJVjpm2tFfqYYD2ERFe/jSipjRK/cdFn2xtcEwxwzjCcPIyuN2khtnRYOfZwWra/gGdM+M+EMzFYSYRCrQz2De7zBPxnKAkzhQYZvAOvAZefDNubC8Ab4vP+fYHllM7AVM47pMzffWwM1jIPZz5/lyqHg4OxYz2arDiY/X3Ka+6/NLTEEYmFquwHSWqrgJPYtdDDm+SRxHDKIz2cWWgQKxDNeTjn+3DSes9bOCykn+cyhlNBEWCnd36zASCAq0+NNpml3dIgNpIKSEQo2CFJzmmepd7TFf8hDcv6uVLqvmoT4JRrr6CbSl2d83BySW0/9Z53NgPCvV0WGqRIpm/5vs8znLSm44B20yo8cWWFF8/CPTcZGjRmiduapJYFPbnK+XIUoFUFnHX7WVTS1UKk3qLjEeAMgPNgomYMK8k9nIdYHN6XMfu5ECmO3Zp4s1H1S0qBL37ySgCcQVIbgM/OtTFZTSuJLVrsXQslZTbR1EZnLBo3XAhwZgvYiYcoMVBpEnSqgeaAMyafPlxJ7TKG0+KdeG2WdVRRUpv6cGJ7J/famX08h9QWhRjO+AKg6zvXb3Q49wWAIKmVUqBDC7lAVpmNSmiQsQ673kbAmbWECICB5N6WJLVOZtX+VCVdMBmG737+TKDHsnZDc+O8G/ANf/z78Pd+8rNhH3lBg0KDxovdj754mhKeH3BQMWPdyKwP55NX/MvknR/5f/vF0/u+6SDgVI2/X0QoZLj3fkP4/y773BJJrW/nECS6xbUh9nGOReQL5EwStRBwxsAvqeOzPvdM2YLhnAOnk9tY6OGURdErhQb5lFodmpcfSqkdOMMpZJZSyY91mLrudF1c7uGcZzhFDLk5OJzL+nCSHBfOS3IbQV68DvsK4LTO+/nrDKfKQu1649lQgElqY0rtuA/neWdwnTGctcVUDDIi7yST1B7j4XRi7OHkbKb/gYWxhYfTWCjhgzscMTV8ro62gjHg1N0dnGAH3Hhv+MwM4LQGWlh84c0V/mnwcSqYSYZTwFYLDtayez88Py5cu0Pt2cZflOZRz3AykMmPZe7dGywYnOGsFZK2vcFjuAvFrTs2fzaMdbiMHYYoqfX9E9VwflRKLQ8NklloEKWqjj2cyyS1xHAKf4zRV+kLtCSpBZfUXn4yBQ+yEWWjzKaSGFNiOFNhLvX85JJaG5nJmhrAQcZ3NjGcHHCq9dW4/aqHswCMfDRKxITY3sn62qD4fWPdMklt4fGXBxjO3jj04ZkoQ4neffMEL9wP+zaxBhPsOSi3nbdFCfcgZzh5aJC1MK5gOJtphjNJamU6T48A51t/ONmggTks0yoZTroBwSazyphK2QIQm6DnoUHpxn//k1fw0ZdOPZPB+vPt0USZpJQCL7vreBVXfWgQpiukQOiHxBhOq0+wxj5OXnMjA7KVqpZ1DkrkC0sAEMqf4z42+p6X/LmQHmhdkJDMyXpwXGiQ2N3FP1t9G770zg9MfkbRJBdTarfAt//7wHf/DvalfQY4eyiIMLFEDyd57GaA9aoPSY5BUgsAO7GCqkxSs6PCcJ4Hr+GNE7+fPKmSFsw2Mk5JUmtcApz0MlFL2Mrw3c+e+upf2Yz92HG2NzjvDF459cfmGc50f8nQh7MssBjrHlpLFrq3LrUa+8H37jvvDJ646u+NZz79PcCX/BrgsS8+LKkNgPPyzXfi1G3wwXd8i/9/uj/Cn1mbkomhKIIfGAW2mChHmlEQsHNmJ0KD5gCnZYBTLvBwupLhvEhblAUMp60UvTST1A7WQUnhF4+HGE7FU2plJqnlcuPJ+amQ1EaZ2BIP5yKG0yGTvUVplkl9TwFsxL7ah3MIioEaw7lqZFpQWW850SE06HHcAYAU8AE5en9sO89wuihFG3//PoYGBY9oeEccK6l1clzcKiW1LjCcWiRbR3xvCyrUWmTZBLE/dpLUkvT0yj74MQPgnLv3SYr8zV98Az/0iddw3g1ZW6NsCDnZu5l7OCPDeVHFAGM4B6EzFkZl1pnp95BniWUWGlTzZm87g+9Z/UH8pv13px8WvbiNczgRu9Qfktih7j56t7wPJy34r2QMZ/IpZm1RFjGcycPpFWQik7kqqWAFk9QG1RMuPwk8/v7qJolU4O+t2DOT2u1xmwIBR/qZKBjOit/ZChX/X4QCDgeceuMZTstTarOeru5AaJDFfrAY3FhdELdRpNQuYjjJdhIDu+oezoYxnJRHUYYSvfvWCZ47PSCprbDEMTRIVebWqofTn0MLkd+jgbCoreVojQup2LPzSFL7lh+e4RzQD0tTanX2pw+FmQGcqIcG+W3QAqGPE69gOvT3v+MKXj/rcG5CIM0QGE60uNSG75cCv7H7w/jzw6/zoUEzHk5KudOOA86Nr4rPSWfiOTjMcGqMK0ZONVmaI01QUwwnLRa2CCxsLSWWDar6LgEZsruHlRiw7u/UP+AcpHBBUhsm6J/5B8Bnfww4Y33Xhn0EpNQWhV7a8XoTIJgBXqshMHFBUgsAHdpUMV0yGEPOGc6zvf/Z9QA4M4azqJC7kaSWpLTpz4MpauG775gGPSZeREeMEmD4qmACLsQsl4ULY91Da8lC332yUrDOFzW2ncGTV9cAHFb9XeCxLwqpihPSynBfyLAYef9v+EP4z6/9D/gfPxSuPVW6w5/b7XxqdHpZUWhQfqwRDM4sQvlix2YMZ/r5EkmtZ5qpKr1AUqsuuEBGsrjMMZwjHzm8RGoIMnFjvZfIS2qnNhIq2MS2AF7qylJqOTthp657saiOQRg1KSUNqZZ7OIvQIJctitL+rdFXJbXGOt8nODDlfKy1Ym0STPL+Awm0zbRFOe8GXMV99O31sK91SW2r0nFKWHQhpfYYSa2TeuQRtZzNBOCMzVhp7sWCUHWGk0kSDTWXD++sK/uQIh4A59xcR4Wfr333CTpj8bGX7kNhSIXJ7MMKaqLgYGxi+en5cfHZO3KuZcc+iCYD7PxYRM1OQsNZmNiHkySg44eq6/Z4RryKa5YF4cViTGDXjMMlcMAZGOXu/lGhQfSZq+umYDhz0AYkD+dsSi1b70VJrc3BnpfU+jVKXL/9mj8H/Id/rbpJUfG8jxlO+kz6rsj+RYbTZJ/lgxhO55z/U0ioVQKc7YlnOHkKbp5SOx0a1Cjfh/P+fvBWoimGs+jDuaQtSpxTqO3WQYbTRuVRWTh4z81LeJE8nFNzdCV4qc5whkKAM7FwaEaAswwNIoazHhpE/vGYgPsGZlG8WcbbHnBCNmjEYUltnIQLhvNQn0Xl6rHOfBs8pZb3EvpASKp9betCSq2/cUWziYsfKQVewXVssU5tUSZSavswwWk3xOOwNMF359Xf4YNPLG6itxAPdYm/JwPgDBVtVfgDy2GcgxQWe+FfOqabB5w2MpyHH1iSG07KjiMTwxjOj/1D/yeXFxWhQT2X1NJjtUBSuzYBdDCGsxMr6GMYTr5fjOE8iwzn2MOZGM6UCidiH86UUkv3fSOGg1JG+u6dW8GJZf1tZzcXrmcKysgZThEktbJYbA7WHSwgLR2c4QT8QrozFtc2Da7r3gO/9jJePnewU/IzYnCCxEatLuE/+/f+HTx/jxZdOcOp3byHk5gpoXRITSwAd2yaPQ0Y+bWpAc7OqQOSWqbIiKmLhyW11cCMhSMWIGaec+PyewTwBSHrcobTJxwfkNQWKbU8vp6Dl0nAGcPRgqSWUrpnJLUi+DCXhQYV1f/INJvUGgfAWnTYDdOA000wnNEKYv37kSS68etiWxQxWiyRh9NsboZ9qgCRweKEnQoNnxYfLQ1LR2htxhmCTG0DP79l93MGOEXwv9r8vcYYTiu0X1wHhvNaFxjO6+8Jnz38rL3nmj+mT792Fno9j6XMlFJbB5w2zsERcNLzdGSBTTB2t/RwKvZ3MSfvD4tsIcRICslH090J35mff/4nMZymYDgFXPJwLpBknrR+P25dbuM9ZC1PlU33+lEptcpLal0pqQ1ybB3uC0HFm80N4ORmdZOydq4IVBL4UBzMpPsUCP5MJCBaA2RWKEiYKN10QkGvUgEtAk7u4WR9OKWbbouilUBnLO7vBgyQOSPOj4cznME7f2gonfeklMi3Q4PA636wuH3u71eyDtF4960N9i78bIrhjMXJ9B0EXLP95aFBzsI4L68GAEpBHvXhDO97XSEPYgCiEKlY80hS+zYYgX07nHxYeDgDYFMwswFxYiI0CAAL/WCSj4LhBIBXzsOkE0ChYvHWXDMupQiG8voOUTCSxpAim0N8t+vuV3+nPBYaWSsF2r4dswsAIHTrU2qJ4WTBDbVBDOcOfh+XMpxLAKeLLSMmwBCxEdzDCfgXD2eBTZfugZA4TJUs3hbFb2wacJ4YktTeiD/rRIvmGIbT1AHnOTGcmwrgJJkfMZzWhYq1ZzhjSm34s4E5fH7Dd2/RQjWr+ovoiJEARviz8HACCIElJbvx8BnOTVjI0MvtpFV4xzoc3+oKfuATd/0cUZkMKBZdtYlJ+oYvegxf/b7HAQBnxGiS1/PAeRtoUS51VhygYRcBTlY8qoQGdWhmF9FcUruocTXdTw+QUkvXYpbhtDkLDviebTylljyck3M+LYL581+m1LL5ozYXxp0B4rFbUgvM9uFUsW/koSGAYlGYACJnvC6JriqpNdahFUN6D7HhPZxJUjsYNrfTt0Xg7PeEj23wcLrV9ZCYOb6nB2ux4gyncOh6AyncUZJaSA0Fm1kGDKkAaLj8nAhn0xwnlF+gO4s9l7MzHxlE8KWHufx6/xL2aFlo0PT9TM/a01cUhAA+9er5JMPppL/+tXvc2BQmVUrUj/VwOgZijNAZyJRI52k+NIjaoiDJAivnYdOFVOOaJYfUBJYYTkqpTWucmFK7gOH8gscv46/9tl+CX/GBJ6AUA3Y2AUQax0lqdWg7J2CZrFIGSW0EnHpGvRBGTVKbQoj8MWae2FgcIIYzBEMWrCgfvg2UjWspJxQaBjj15lr4YAKcnLGbYzhbJTFYi/v7wSu7Jj2crA+nsQtThvP7WU54nWNK7WBx+9yfe7IO0Xj3zUvx3plKfhfFuQWAr3r3DfyeX/nF+MXvTWuyxHD6eSMI/9OxzjCcNbWaNTYp6eievEAR9ufbeAQ4Q2jQYUktMZy5pHbk//zZ7wVe/dn0exOSAL+N8HNTl9TeurzCY5dXeIlkAXsPThSbOLhuXQdJ7ZSHkxbhynZxIiXAOewPp6JyVmSoLLLylNp0zEKVDGcu16xvx6KLDOc8+CI2YAmrFSvYUwsEnmantL/Omxvep8cZLCapJQ8nAc4oqV3Qq/XEBKDPJbVyXa2KTQ7OsHBJbWA4a5JaYolKDycxnDzhDsCiZySGWqGFbtsHZjjpuaLFV9mHE0DYV1v83sPzcA4Fw0kvt02r8MQqnPfVFbxEp70mnwnXp2nyF+I3/8Kn/TZPw7O3mOH0wSpCyqqc8VjAaU0NcOr5YB+TrkOq2M9JasPiSC0Ap1NfucTD6cay/ia2z/Fp5Cqm1E5tJDCcWWiQSo3knUsML1Dts+a3k0tqE0g4FBrklljqfVAPW9TFBE5nM8ZrIw5JauuAMy5Ao4fTYGC+1tiIvmLjOA8eTrG54UFJ5V4y1mEl04F6hnOcZXBwKA0tDPaMxbW2AMisqEv/Tq16kqS226dnjwAqLdh7NNE2cbN/Ca+pxzOp3dSgeXCFHk9d2+BTr52F0K/xeRfBw1nzc32p/Rg+YD/u943YrYt6ol069kE0UI4znAyYH/JwQngPJ6YXzevBS2k5kC2fjcFYnGCfFFcsbIf6lS+wAAIAftn7n4BWMhZ2PMNJBf2xpHbdzNxrrO+6DKFBHKQJ6Z8TmrOFGocEjUaU1I4ZzpGHk6WiRmAiQlBPZEUrktrIcHqm3wkF3bI+nOvL4YOM4cwktXYScDZKoh8cTndDsM5MAc7cw7lEUptk0KnYUwWcKklq75x3WDdydB3fc+sksuNTktr43BaS2t/9K74o317YB+n8vOEhOQecfu2UsaIBcDauGz3PfO4BK2S+1ccjwEmBNktDg4qU2hHD+Xd/F/BDfz79Hsykh1NEBmyILzfOcALAU9fXuEfvgr2XX2qmxefPsJIiVL8mJLWBKVIspRbBSN5vlzCcFvtg4K8BTmsxkrMBnuHkDBmBmHnAabAPkjZ7wF9KzO1+AcgwlOA5teAtWxe8698Gvun/ApzcqjCcPKVWpubZEXCGhbipH6e1DicugI2QGgcAvWjR2CMktQwwGFY4OI+AMzCc7PyUfRFd8IEaUPJrLnvWGA4+I+jPYYSG1C20bh+Y4YxA0yWGs2TQTSWV+WF6OOm7ieG8EwDnSavweOPvpU5dwuu78CBWwAc9K02TL0Z0YDzjPWnSAncOkHmG0ySGswScC/pwShhsQaFYY8DZY5z8yYdhIWepkfn0OY9sEkn5LyKpXZBSmzFb4TlsFAVhpZRauSA0yHKGU8isnQFfLNbsBXw7cXFNhYA5uag8IjTIucLDmSS1nIFdTzGc9DzVAKeWGcPZG4sWA3abd6RdpYCPmoezD304T64HQDoBeBngVDAYhgsAzmDZ4MdYMpzOmsx3K5wtJLXeO8sDu8wwRL+0C+E6lDtwdXgdd/VjcR6abfFFx272eM+tE3zqtTNva6ndB8HDW7vHv038Tfyf7d8AkJ4fG4PpjnyestCgoi0K93DOpdQGRcwhD+el4Q6AZKUJBxC2EZ41M6ARJvYVrzGcYgHDyYdkDKcrAB0AnLQaf/5bfhH+w69+ZnojvA9n9HAydlH5ljqtC3YnNX6WRoP12EyD9o/sOKmIF/3JxHqGJOO5PpwuFGJT+428D6dcXQnbdzMM57SktjcHGE5rsvt7WNgWJcr0zbykNmc4+xG7CfgWc1ENeCg06NB8k839NrRAoZ85UGhQRjaH871GN1o7xfenkNm23+rjEeBUbUzHmxtTHs5GFAxnd5559ua08KktyhBftLLw01xdNzjtw+8HhrPhgJM9xFqGePcDDKd2CSwJTQznYQ+ndMbLiFD3LeWSxzKlNjGc+kCrDWI4e+Eni+UM53JJ7dRinBYlUe702/4B8LX/WQiFKRjOcA61FBigkzm8aIsylRbaGesTggGguZQ2Lddo3DEMZ/rsa3dSMAOFBtFknPXhpLYoksXq89AgJmkBgBbDAkntFnuxwlPX1oBq/KLqAQYVEgbGbJUeYc7GxmOzblFP1mP24RJJas/8/bNpFG41/ry/tNepkloL0xo6DE6iafLFiAoAlJ6lDLjMLPQG8rJKXWU4o2z8gMxvF54vNzDJd/idHnoWsCYP59I+nMQIXFxSaxcwnM6mUJvo4VTSsyQ8pXamLQqBySGT1PKUWpdCk1Ccv2yHcw9nlIkVRUU+RPDwLfFwokiSTKFBOQO7xoSHM7Q6qXs4OcNp0A0enO5OUl/B1BdwzHBuuwHXxBnUyY1qUQTw93HLfJYKFgN57I8BF7pFg6FgOMvQIJPdnz40KBUmKIil2zPAaYbUz1T49iHEBG7sfez1lUUMZyy8DXu859YlfPq1c89iVoA+9WGt3eON630LLSAFjfGC4REjMTsKRjQ+SDDuL1u/zGUJhN6DmYezYm+4bIMya05SOySJPoCM4TQiWVeOGSnMjLGBxbP3q7/iKTxxdT363TiYh9NblnxKbfJw+s4AjVsuqU0SSla0ohYn4TzK+CynfeeAM2M4K2DJhs9Er6BUGYiXq0ts+2H9VPbhnFi3tkqitxb39z0GJ6FQec8zhtM559sqLZHUqjTnAP7Zq0nPeWjQnfMuqrj4EELgieseWE9JamuhQdUh0nNuic3MfLYOZoLhXKEfdVCIKbwZw/nIw/mWHyL0iDzUUmPaw1lEmJt9mkzhTcnTktoEOGnCLSesqxuN+314UHd+4m7XCZxwX0NiOOuLOVo8S5sYThnkuf0CwCmcicmxptIKoGxbkQ5zFeRSQVIbQMwUA+arci62JbAHPZxhkbyE1YqL8QmwOyXpajae4aRrbfr4UpRBskfNn20BOKcWA/vBYiM6/3lWGe3lKr7AFg0GTu7cTYBzjuEc9UU0NpPUxheqS5La4VDbmf4cO6zw1PUNnPTP1YNEfQ8FwPAMel7QcBOA07p5YLJ00ML/ZFVKajVuNv7vz51r7BGYhgobb/s9euiRV0iH1FobGNChZ8Bl6gUJLqlVoSVFefzzBR36P5Ksu0ofzr2b93DyPpyRsZvzfEaG8wHaoixkOMuiV6sEjBM+hXkBw0nPqysktbzNwiKGc0JSW1sgxhE8fMtDg5ikli1kbQE4a304PcM55eGUWR/Owfq2KN0lBjhjX8Cxh3Pf9bgqzqFPbkR/5Oj7rUOriKlroWExEGg8SlLbevaVMZyWh0fBF0MyFtLZ1KaGhe117L1mQysVFRnOxASe2HP0+nK8x6beuf7/wjENe7zvsRO8ftb5HIXKMQopoYSt+ot9CYD8wOQ9uxjgjAyjkN7DmQHOZR5OERbZUiDKREvlwn6wuAm/bsnCDEvAaYqCPgNH1Cd2iYeTD6kkrPMhP4nhPG4bnGDQst6H0wbftf/OMfCp7Jj/M/MU52xl3halYOFCUSp5O6cltcYkDyeF2OzQpqLXlIfTHWA4BxdCg/RBSS29h49iOF0CnPXQoMBwGmI468zyO24G5diEpLZUw8zsWPw8SWp5CnIKDWK/E+7hNbpRAdyxYlcE5o88nG+DoTQasUBSGxnOsi3KkCS1zvnFP5tIqOlubcQkMs5wFpKMa5sGpwMxnF5S265ZPyWZA845D2dqS9LHflEkszBLGE4Y7BzJACdSakV6kcXf0w1WYsC+9zHd+gDgHAKTRSmRh/tw+j+PCQ2aWhynMJRiAqKKKy0uTclwsjYgMgecU9/VDRYb7P1xspfpIFdYuWW9UeO+hLE7v49t57/vfsFwcgY4Lqpja43BS3ACw0kvQLpGekGSM/otzm2Ld17beIYTC34HwH7I/VfxsCgyn4BnLTSo4h8jYPIwZLUppZYktSk06Iby5/3ZM4kuSM273biNgB069FBYNQXgbAPDaQhwFinIEyOX1IrRfeIWejgJcNYktd7DOQc4E6hTCzycMSUy2giOLwYkD+cMk1pLqQ19OJ3xwElJAa2mGU4Ca6ZhbVEy6TA7fhSAnQ+6L4u02nmGU0EJt+j0SOcA3oczSrMSIDbNJaxQ78NpbGh1UtmftVZ5H87BoBUGw8kTsGFhGiWLFYZT7oNv7+QmLFRV5eFDi8Iuq7aQ1C5gisIQeoUWfTaHRClhGF5Sm/5fZN44FSW1JcPJGaJBNDFc5xLOMDRXsnM+NeKcFRhO/zMbwWJ+MH4/ymKZC/tBLGEEmOoBJbVSwcg2A5xcmSLnsgSCh1POeDi3vcFN4dctGTApUmrtDMNpwzEeCxaVQOqbyUJ+jtsI68MpgqTWpd7rkop+oN1fADiZEiGOgmmLad6TDCcDvRUgR4x9lJazEMROrKHomZ/wcE4BPSC0RbEWp/uQUgvW0zYeVwKsQwScCxhOnRdQ4r4Xo2V9OG+fd1VJLQBcuRy8qpOSWnqPHWI40/1NgDNnOCk0KE8NN6LBWnSjtUjy80t2PzwCnG/5IRZKalXJcEbAyaqRdgDgspePgoGrvVgAOIrQtgOGsGjRRWT+1XWDU1rPBMC5IsM3cpmJOtAWhfaThwZRANEiwOkMdnOS2uC9tEJnAIqa+fZ9nwULTe0nSScpoOKQh9NEhnNJaFBgOCe+Oy5KymtGFVfal6FLDKcQiQ0AxpLaCX9PZyw26GB0LukZJAGBhT7OcC3uY4PW7fHPPvoyAOB8P8dwVhYsQSpSk9QuSam13Tnu2wZPX18DUqNZCDi/9W/9OH7fd/3k6Od0PXlYTAITfr9rHhL6/MMIDqKX5aYMDWoUrkl/fX7unvSprgC22/FzZPouMJz5s90QwxkWW8OwUFJrLLSwkEr7NMJRaFBgbmZeYAoGnfQLkForiA4NxCyAZMBApoUKAPzr7/i/4yf+/l/K94kWfA/AcP4i+2H8Yf3XD6TUjosSjZIw8G1eYh9OISYZcHo2Sg+niPLJPKV2sjgw6sNJjNpcSq2fN+dav8SPlm1RWPgEXR/bXELruonQIG8JmUypdakg2hP7rlfYtj69ka6lT2vM91d1lL593b+TJhjORvqfe8BpU+H1iJRaoVdoxdjDmUlqWesxIABOdj1cCOvhKbVuSJJaJxQMtC/WWotLbgvTXmFhIss8nO8NgFPDVIE+MdzlPU7vTTqmUVuUoyW1CcTYQlIrMcRilFrUFoUxcqW0uje4EQCn4u/cEcMZ3ssECJnfkBjOo8lJ5UPVrDURWMz6p2uDrfdkZDhNXOOJwHDGjy8BnJW2KK5gK2NAmXUZG+1/P5AKTBY9GqFwQa3EHGvz1slVneFkbVG8h7O++42S6AaL0533cGqY/H4tADL9X7OkLQor0lvL5MDFiB5OY3HnvB+1RIn7SkFJk6FB0yxx/sHQax2DLzhAJPmvMzFASxc3qVUrrNCPGE7D/fy0Vn4EON/6QwYm5lCPwbk+nHFdRgChjF+fuJnTQ58ktRTEQOPqpsG5CRPU7i6sE9hsmIeT3eD6gKSWUkal7eNx6DYAzm6+2TyQA05T8S3FPonFBCHDRGeGzvdziwznNOCUsDBB0uYWMpyLAEZsizIBOKcWhbpgg8w+a4sSF2dAklBH6cyEpLY3WIs9LJfugaVjzjXd5iMsCvb6Ci7LDn/vp3xT8rPOoFUSJwEscUBuGUMV99EZGOcDVmhBQoulBsNBSW23PcMWK7zz+sZ7o4VZ5KV87vYWL9wZg+syldRW5JI1D2eUWD8EHydJ12oM59UAOD/8mo0ezl2N4TRdVVLbrIjhDICzYy/FOYaTBatYiNHxO3ug1yx8IaGXBWvvdwbAYQ9nnOOkSl6+8PlbH//bcB/+O/nnSSJ1UUYGwC/Fj+O36f8FZua6WjeWXTdKMIbTp9RKKSZlq8RwxsRMICzq2MKAsWXTgJOYzXxxLWbYO5p3jFkIICrNyWFTc3LXXPIF1coc6mWypsomrqiVTNh/Cr6SuoW66oODrp8EDzBkWriFobsg7V9f989opcA3WItGhDYfauV9+xcIDRLaS2o5w+nCXBFDlazN7meZ9eGUjOFM85AxQ/KNB0mttj3s7h6kcDDt1UWS2uTh3OE9t/w9NXXehax7OMm37UMKU9ALKQaOL+AwSa3M/fbaDdhLv5+1pvVxXwlwQqQ2HsV+bDuDm6gwnHTuibEdyNM2ZjipIHKsh1MFf2UmgZ3pgVvfCK33FJQErCu2JxVsxnAuCQ0KoDJjfOl6hLYokTkfAHhGLT7rJcNZbYuSPJyRJRQCe7Q+G4MHF1VTaqcltY0S6I2LfTg1bL42iOx5AJyUHXIkwznEZ2+a4dz33sM5xXCu2sb3qp5qi0Lz0oJCRCycWZ91UTKcBnLEwhu18pLaEcPJZNK1++EtOt72gJP6cB5ibxLDqePvASHKnW4eqqIwgEEJd7URJxUzRO9KKam9ummimdvs7mGPJjYsBuoM52RoEMnabA+E+O7V5ggPJyxjOGsLmPCSLx5eFap+Q7dHH/qsARhLMcKg6rQNDKebq7KCM5wLFrG0+JsMDfKL9VGQRslwmi6eQyVzhtMVktq50KANupxJAWAuyHDu9VVc0wO+7yMvY9sZnHcDTlYqa5Icj7NgOK01EDZJaun8UFFgiTzWdmfYuhbXNs3i5wrwVfCaZ4mKQEOV4QyAkxL7+H5EifWDezjpRTr2cCpcFjsYJ/ChF/awQa3Q7cbXzA0deqdHDcZjam24fhnDOQM4iQ2QSgcPZ53hnPNwKmcwBIazBjg7txRw6iTpCtdJwlRAcNgn8qhfoJpLxzPpmUTBbEXAmXrLkodzjuGMcvOiD2dagLms7+FkaFAhpY2hQbMM5/K2Mf6+ZwucSkqtDWFkruKDN9Q6pOI7W2UeThstFEI1WF9/JwBA0+JQiBGb3hLg3NzwqZpVhhMxNMipFo0wqfJ/BOCUQVKbMZwWeTCPM3laOJNZCukltQoOe1b0ccZ7OKVwcEJhkA2k67E/u+P/f3U1AuPZ0KAoqe2wbhTeeXU1ySyLYIkpi3s2AAcNDyJcUbw42sPpEoixsgwNGtDJDawTULOhQbTIBlJKbb7fO8Zwat7upSjGxOtORXim+nGUN3Gkh1NJktSmFjgXltSq1BbFsaAdGe6d+PFFktpxGwxRsIJ0/1tr07UKg/yZCaTOpB2bnCV0eo31yWV23ybAyT2cEtNhlw3rwzlAQ5VdHsL2PvTsPbx0bxffw0s8nIKpwuied5X5sgnv0tfPOliHSYZz0yh0aGCm1lK0/lxwX1Bxm/pwap3OlwjhoGOGc42V6KcltUKy++HB1ytv9vG2B5xKB6/ZAkmt4fQ3Yzjjy4GAUQk4JyracfKzA1tElpLalIBpd/ewQ4vL67S9EcMJlUmJ+OiHEAnj0iJjfXI57PrhPpzKGR8mgvoii2L2y1Qx1SQZbsckS1PMsglNcW3wUB1kOMMmlrBphxI8ozernMQj4Az7wiS11BaFhigB54Skdt97D6ctJLWGet0dyXB2+io2Yo9tb/ATz93B2d7gUqshhPDJcrwtSkzFI0+dDbKQvA8nLZaWMJzot9hihU2rRsnEc2PX1+8DqoxyL6cSgbWgkIpKy4WjQqQOjJLhfP0stEVpNC5hi/vY4HRv8MSNq/5Y9uNr5sjDWUpqGw3jRPRwZqqBOUltn+T9tQTQ5OGck9RaWNXCltVfJqmdbUQdY93HDKdyw+iapD6cBAAuDjin/Dj+e8atc7xf0wPO3viUWjnTh5POn+MeTrYwcEyyCgDCHpLUElBe4OEM87lZACCkcxm7IjJJbfjO1s/vrjKXUB/OmrSzVdMMJy4/GXYgeThLSW3TJ0ntdGiQZZLaPLF5VnZcDNmsRgynnytsBCu+NUbp4cwXfQoWfeHhjGm3QsEKDe167O/f9h9YJYZzPqWWAKdf9L7vVpjfJxhOVfFwDuG+pv+jfXfEcC5lxGkEWSDgJasanOHsYWSDvWiqTevjvoaUWilEvBdscd96Sa1vuabFkOb5+GyQRJgktdMezuNTasN7mYUGHXNf+S8lDye1RRGR0QJ88YgTCsdIarOiUgE4Y1HKWr//fKkewOQcw0lsnOUMJ4D1+gQ3rl1L61gmqeUFJsH2pRyNkuiNw+muxwDpe9FXGM7/5adfxvd86Pn4Pi7BWHWwPACzgOF86Z5/pqYYznWj0EFPdjqIxaAFEn5qR0OSWp0VTy2Mk6OiiFMrrCqhQZYX1h61RXn7DDEhqTXW4e/95GfhnIu+IMt9fbSYEczbRotEthhRzkwynKtGh353A0yQlOiKpHaglgu7U+zR4PKqDjgjwzmVUksLDCAyWycnl8KuL5PU7gX5Kmt9OGmCyF+kNAkPQ4+e/d4UIImJdXrlU+amQjno80cADHFAbminKuy6YB2ZpFZLEXuFAVxSeyA0yPiUWlcwnO5IwEmN5/v2aqxI/5vn7+K8G3Bp5fel1TI71zHFkjx1dkDeFiWX1PKU4cnRb7FFi5NGxedqyTXZ9bbKRiZmM+xzLGikc20/Rx7OkwA4725DW4RWYWPPcR/+2j392HUAQF+R1LopSa3y7XQI4JijGU6S1E68zCZ8ykBQF8jG37esjRPvwzkHWJF5OPMXpnJmdE2IYVDRw3lcNZf6IQKAmAOcGcPJPZxeUmus9QynnA4fih5Y3abFjpBJ7uZc7geclNTSjUuqilxqVh3hXWEXLT4K2ZtMC8YIcpvg959jOCtMm1aSbW+ACYBT6Qa4/ETY17A4FGIkqW0JcK6vT7bqGpiHkxb2ca4/wmunmvWI4YzpsrGgllguwEtgS4ZTwqJn/aWtSSm1kBKD8OE6xHCKzdXESB141vwB+/v2C2+twiHWPZwS45RaGwC0FgbWObbv9DwdN9fJMNcDgAn+WbpnFAyM0NijnfVwCufCIjsVO+KcEe4HLqnVPH25UBrR+qfGcMZE/WM9nAEgWvY8qKMltSkkMoYG8T6cUmYM53GhQdOAkxe3yB/If1+y61VTAzihIIV/r9L9C8An1QZ/7OBk7uHMJLV2VlILALfPexinoISJxWEASdEBgdNdKlQvApzs3JgCLNf24eVTf39OMZzrNgDOiU4HiVleLqml0KDk4XQQFCRUMpx67ftwPpLUAngEOCF1Ww1E+YkP/Qi+6bu/Cj/9kQ/DON+vrAo4udSQFh48pXbigQF89LyBAmwf2Q1VAM5rmwZ9SMDE/h52Lmc46Qb3k76IoQO1Qc27/S/6l97JeoW907DdkpRai17mQSd80AKmZHR1k1qpkE/NQviKcgUU0IJZqsDuHpTUUiqpO7yQpcX6ZFuUIi0vHgRjOK3111il0CCTVSDpJUWylWmGc409wJkUIIUILZTUUjLqsLoGYQc8c1Xjp56/i/v7wfs3/8qvxO+U35MznLZY6FlbTamlyncjhoMATgxbbF1gOLUP49ovYDj3ffHCCsN2O/zw6nfhA3d/EEAKk+Iv+FpCZrofli/CnHN47vb4GbARcCZJrZYCrZZYu3Pcd/7l/e4nfJBK11Uktab3gLNIqV0pFe5vf88Ztth1Mwxnkh3WJbU0/0z5ypxzkM5AhOcrA3DUFgV6/gXIPZxFrLvGmOGMMff6Yp6zzJs5U4Cq9WptFKVL+sLir3/tL+EPnP5RTBH2xF5K3rsuk9TajMmhItZ4Q7lsMG73QEqt/9UFDCccqh5Ox9qitL6gKIc6w+kltfXFmoqJwkMshsimBa497X+umYezeOesBg8ysL4WFmr1lNomtFNxumA4jwAGqllBCYeOg8UIOCmYz2TvZYC1thEihgb17Pl1xi96RXiH+36VA4bzkMC7vhbvsak8AiDNofQee++NULw82sNpYqBQZOxUAtRHDZf6LEZQHuYc7QZYodGhnWU4EYGQSIUSa4FPfB/wJ74A2N7GfnsfJ8JvQ/HCPs1NBE7KQq9KDCcVRI6X1Ia+mQ/i4QwKAbSXYh9O3wbDem8gkBEKulng4awlG5cMJ0+RRaFkiKFBQaU00RaFlHsZCbC6CqyvAUBQxyR5cGQ4nQ1zyzTDCfh34QAFDYu+EhpkIHG6S3LSZoGklrO/xkyHBpFqixjOWh9OAFhrH+hn+6l3xsLQIARJbWA4LWQEnP5dQD8rGE69CaFBhUSeZ4Ww4sJbfTwCnLqBFC4FcYQhbn8KV8QW7van44s5A5zcw0mLalokhhuHosyn+nCuGxUTQanCp8o+nOvk4VTdKXZocYUxnGRSpoazFtNtUXrj0FLj6AA0Lq18JdMtApwmJahWQGCqBufHKxST1Ia0w054oF9jOC2xvUqjQzO7+AaQSeMO+fbi4nBqgcArT3xwhpMKC6Ga6T2cvBhRhAZNejgNNuiyRD7geEntPrDTduVfJF/91Ao/9dxdnHcGV1oAz38QXyiezxnO0gMUk9byPpy0kOKymf/kr38Q/90//MhoP+TgJbUnrYJUvhVOV0nHLMduqEtqxf4O3iFu41b3rN9nYjjZ81RrA0Tb6oflLNq/+NnX8I1/4vvx7Ov5c0DbIqZ411tsAtu5Mmc4g79W733ypv/OWvhWAJxt8cJtdPD+ViS1tT636f8CS690WgCxEYHNFItP4E2qADgZYHIpNGiO4UwVWubhZGz4iHUlf6dKEu5jRpZuTRLyweKX//f/DN/7kZeyY1OCJLWJ4Ryg/DxrHZ7qPoVnzHOTfTitNTBOQCkZn3G/KGChQZmkdgJwxs/4pMnoYz3Qh9PvwwK1BpIsEsgltTTnuJVfMIsJwNlMMJxAKg7AmmihkLoFvvI3A//77wYu3QpHN2Y4pdl5MKJXXlJbeScZ69BQG61SUnsMwxmSKLPAH8oTiKE6+TWTTHYspI6sUcZw2p4BVxW9jsP5HQCAPrmWe+Gm9g/5+uA9N5IvsBxCympKLamHdAgNKtsMHb1YdSlQyaj8na4xeEktWuhZSa1fZEuRpODOWeC1TwDb14GXPgx39mr8vOZS4VGP2oLhlDIVQ1V6zx4zPMPpC02pD+eRgPPyE/5e/9JfFxhOEYN2CATylFrFpMCTI/YtZtesTKllbTi4/Nn/p4Zist6q/zD0Bu2M9fMhfebX/QXgm/9rAIARIewrbMe/+wVjOOvnm7yYt88IcA55wZjWv5Ce4TyiLQoEyZZN9ONP+blbLSPDOdWHc9MqdE5P9nKP78gFUmsXgphAbGYMOEos9KhXrF5hLcahQbFAJBRjdR8Bzrf8oJeqKSogUebW7QLgHFIAgf9FACQ1JA9nznDGXmAzgNMvhIbIWqii+n11kzycymxHoUHEcMbJWKg8fpyNwdiRpPZSq7BFW21YXw4fNBIktabGcHqJ8ailCAXTDF30AvViBY2hyoAN8Vwoz7QcBJxpGwdZLXqxTTzc05JaxjoS2I4MJ0t4A6t4UoLhZEqt93ASCxF/Xx8HOGPvx/V1AMBXPLnCJ189w0v3dnhK3QGcDyfqKgwnX1TWGE5qi8LlsR996R4++uLpaD+U2WGLFptWx4VQP9TBNg1jHXrjqteN5HUiPk8Iiz8mqRVqxKZdRFL7sZdO4VwKBSq3tW7S/UDy2mbwDOdKSzx1y4P9ocJwwlAfzvyeagMQIl8xl6lXtxP3KTFltT6ksaH9XNshYSFVkNRywBRDg5pZhlOwEDUZpeOhSIFhDHYtFdQu5uH0C/98nj3bD/jkq2f46Eun2edGfTilDFI4L+9qXYfG9ZOhQZRCqIRIzz1r0A3nMgZSVOZC2k76+xAB+byHMyxiFzCcoyTJLKU2nIMQGqTtfqQiMGaAFC6xZMWIxU/Wtkvpxs9Xv+Cb4+f8fJdvW1gfKELs4VRblJYktUUK+DGhQdTP1rBnpmQ46x7OxBA58k4OXFJrMg+nCYDTRsB5Pc3xs6FBlFLrj+19geFUVcCpUevDSYF8Cr5oEu8t3t7iiCEYYHIyP/eR4Tzo4fQLbylEYuatScqcVz8Gd/YaAMCEdckIcBaS2iw0MTx7Ql8QcBJ4sakAdjTgBPy93p5EAFuCwExS2yyR1FLh6rCHM0lq+XNODKfNPpuNIM3ujc1JgHf8QuDm+wBwhpMAZ2JwpZtmONsAHO9ue0ilPcNZ8XBaCNzbpeBAvdA/SySMDevnKcKmUSJmKkx6OLUPDapZwIALSGqZh5MYW992x/l3RnmPkqS29HByOXSU1D4KDXrLD0oVGwHOsAgb+l3wPhb9NElKg2kP51SIDo0NAU7TRwBXSjKurpuMPRuFBgliOJO8Y4rh7IxFIwhw+peMVhJ7tIvAjYQFlMbg5GRokKodbwVwDjLIoCqAhCdadmgOS2rZc3oIcC71cI4lteylTJNXqLwKIWD4vUF/p21MfJf3cO4hCoYzejorrERtEDgRJ17W+WWP++997vYWT8NXmNci7wXF5X3Wpd5iZWiQrgDObWdwf1dcN2uhzRY7rHDSqOTb7abljwBif8BaINEYcAYJIJfUimkP5zGS2hfubsPvjL3cgH9ZkgdzE4CjGu7jPjZ4980TnJx4WfSwr9yrpkfvxh5OJQV6qHh8XKY+TIQc+M8lNqAmZ3QHJLV0HoXU6JzOWx/YAcZ5ifhU2jWQrgmkTkEc4fu0M2OJIYFRqgofCTgH63wxC4AMgJOub8bcV1rntFrERYyxDq3bo0EPM9UWhVIIlWChISwwzrkMvKip0KBsQWliKxVZkVLSmGovUf0sk0XGfQT8YpiuT5AEbkQ3Zs0IKE8AYC6ppVRyXfGouYqPWJgOg6AUWzXRFsVBhcRyYpIpgfgYSa0Oac89e2as9ZJjYjiFM1lfWcHPEYUGCZvNV9aYELriACljuI7deX9qc+l6vMfmPJy6CA36guDh/MDTN0efpdCgWqaEho0sYWTsqBfqkYoB4Zzv4Qvv4eT7pzHAigYdVrMMZ0ypFSnEDc6lddArHwO2HnBum1s+YXeUUkt2pIrcXJPXNb1njxlSMs8lzT/HhgYV23PEcCIlx/JnsMzgqG8osOJZaFDZh5PJbllxgH5fCxvnl1oQkhO+XQkFRdYUA64COEndNN8WhXzm3i7lpdJjhtN7OPv4bm+WMJxIQJjaoswxnICflq9uJjycjUIPXe2qAARbArBIUkv5KM4ZWMcYzlAUcBBjwNmsscJ0Sq3I3iuPPJxv+UEVtZKxi6xDv/XJh8LAyjHgzJrbFym1/qU3x3DKYNwe4iKy9HCuQwALjb2rhwZJmaptU4BzMC55ONk2O7GC4Azn658E7r88+n0FAyGbCJLLkRr1lgxnktQOQQ5IstGuAkgMl9Q6PR3KQZ9nk90hVksekBtGac8sw5lLagHAsrYo45TaCYZz8MyjbHMPZ2I4l3k4yXekAuD8wK10/p8MgHMjcuO6jS9gHzwz9nASW+X3vcUQwdh5Z3B/XwDOcP9sXYtNmwBnf4Cd3vUGT+FV3DSvjP6PACddMxsLGiygqSIhvxjg9Ps/YoGcwy3cxfreJxPgDH5O2Z3hHGu859YJNqG9kKkUboTtq6FBQgQpdoXhnAo5AJL0VikdJVB8xILNlNLBhqq38qFlXBLqzDBiuavDJlCXUmrTPTNqVUP/R8/MkYCTS2pFWAR3FcAZixJAXNhpKb0CIfR2a9wejesnJbXEcMqM4ZRsYWAzRkm6ZQznElkfLR6XtLkQcHBsEZ4ktSYtXlae4VxjDDgda3VSG/FdZIdYDFHNWDLoW3EVklo3wCABzkmGMxQRRCiAugtIagX1eWbPDBV7wVJqs6CnLDRIRkktfwad6bOkTCsbNK4HdvfQOYX15iQxUlPXyzk0JPE2eQFt1Y7Be/Jwjue0yHAyGSSBseM9nIk1o/ZjkeHEACs1OtFCTxVT4CXdFhKChQZ5hjPM+a9+DHL7OgBgt3osAU7n0v3paK1U6b9Kzx6l1B7r4WQSWOe8TL7sk3iR7VFKbWSI2b2qK8/HaNQklPHvYvQZ4YrnnIV5ARPzSWDK95HhHC/14xzPJLXEcIrSH84Gb2/SNE3eqYEdi42SWjv6vblhqThorC9ITcyXBHyvbZpJ9nvTSq8QnFiHxHfcAubbgcKaXNaH07OV3mdb3qMiMJzTktrk4XwkqX0bDHrZmoJyp0bEtt8nhrMiqc2CbyoMJzWNro1No9BDwdkhyuS0HlebV+uU2LZHmwFO0sVrBjjVxI1bCw0CgE6u8lCJ//m3Av/4D45+3wNOCjqpAMUpwEk9E02PYcgBZ40Bo8WWigznIcCZJruDvRcjwzkhqWXJhdngDGchqQVQBErlHs6phfu+N9hgD7nKAWf0dPaHfbWAZzitE95TBOB6Y/D0db+NJ6wHcusimjueY6Vi303BUmpLwKlDT01rHc47g9OS4QxAa4cVVloyhvMA4Bws/njzl/Ffmb88+j/qvyrCgt6G8K6S4Syv5fAggHPELFh8m/4uPP09vyECRpLUiu4UYn0V/9a7rseFuK14LxPgHL/UDJO02oUeTstDg2qp1EcwnCXgtHYIy9rptGv/nA+xPY1S7IXpPIgYhcSQhDuGYRwpqWU9WInhpEVOdl875pljfTj9Isan1LZu731qEwynM6GxtxSFhxMwEN47yQHnpIezkNRSVbtyH6SN+f8zC+5dX2gZhwZZw3pOtlcA+OfflL0dqUXUBOCMahsGOGU1FGV8r0jLGc666sZYB027T2wWgbJjmChFklrOcAY5nkoFDs4aSyRfH2IfTpv1wrXWpPtJKBjZ+kCs/T2c4gQnbZMktVMMJz8vMeGcmOXxuZRShkyJceErYzijJYKKPUdKarn/l95jkeE0sLIJgHOe4STAGROLnU3vx1c/Dr3zLWT2m8ehhPXPXPlcIBX4swwLuidi+7GjDpF5OG2UEB/LkvIhJWJx1ocu5aFBxgnoZlq9kDaUF+j8P0jaSYCTBbGVDGc41/RMVhlA8nBSaFBFVRGzGqLnMgHq+dCgdA6bph2n0XPAuWcM50KwT/sVZacTxSdiOKfktACwCpLaqU4HsTC6oMBlpZeFOzsEBQx5OH0In4UcFTREs8GqUJcBTFKrVKZMeauPtz3gpEnflQwnLQL7XexXVmU4xTAGnJTSRb3AJiRUq0ZhcAp26OPk0VQkGet1klz2ss2qOZTcljycM6FBdhwaBACDWOWyurNXgXvPj35fwkIqnfnO+Egx+3WG0w19fKFT64++MhGQn1XrBns0cYE5NTjgPNT3MTKcEwsEdyiltt8ySW26Vjw4ACXDOREaNPR7KOGgpjycC1Nqh26HDhqrTUjU687wC5++CgC4NXimeoUuA+OpL6IOsiMTXsrKv5gJaFJvxRCstQu97kYMZwDHVm8ghIjsyHCgpc2uN7glTnHZjfvARobTMUmtSEEgAGCgsmtps3thuSfihTskqS2ZBeCaOIM+fxlfpF8EEACnc8D+FL/2a96P//yX/YIUelJhJkXwcNYkRYNIgI+rLOYYTgKcSlNKbcFcRYZzQulgU7hXLxpIxmJYM2CI98B04WqNPgaICZEi9qOcd8Rwkn/xgqFBvC2KLSS17JrlDGdKqR2gokyrsfMMp7PG31eSMZwE5iDhnMsB5xTDyUEA8xCqOYaTs5QHRil7o7Rga1MCqwihQWvRjVptkC1iEnAyvy1JXbWqMZxixHAKO8CI8G6tyN4BCg0iEE7BNQQ4j/DaRVtMznB6Fp8YwCFTmvjwD1rQSlC6u+0Ltp/uO6ngpJfUiu4eTt0J1q2M98VUcSdLxqW5kAqJRTo5kKTE0dpBxxMANPkgE1vue/ke+zwJZyNQslFSyxhO4RnO5kAfzuThDODL2rQOuvsZbM4/C+MEutVNz3AaN3ou/B8kMax4OC8oqY19My0li14cbAKIbVFAAFakIj8ADNDLfIqC7hnGuJNEtwCcVAjOwsFiYSm8H2vy8+DhJMApJgCnYG1RrEvHJ8Wch5MxnG3r1wbcc55Janlo0FIPp89liGnsE/J62o+plihACg2asmUlD+ey0CDFPJyaij3W+Hdw5f6UTZ3hjOoKlg0w24bsLTIeAU5J/sJSUhsqb/0+eTEFZzhlilKnhW0RGmSZHKc2NiGl1gw9W0SOH57NmjFpMn/h0wQX+//IaUltP4xDgwDPNlL/RgBAdwacv57/cqiwSqXHQSO0nalUMQL1QxcTNglU9TWGM0xeOjCcc333gJLhnH9oCfxNPdyZtp6PjOHs8p8hZzhjRe5AoITde5ClSoYzeDhrzdoBf1/9vu/6Cfzkc3f8v/s9OjRYn1DPvS2+/OnAdvYeJK3dfoLhlCxYwfeMtRWGE/B9VM+7BDizFjRhX6mlS/RGL/BwbrBLwRp8VCS1pdLASZmd3+GIe4GGsQ4vhbS7MqzDWOtZVQBfjZ8BEDyc/RZwFnpz1Rd74j0+vlelHWCEri6YrEgeTscKK6WnPNun+CJuQluY/P4SCxlOhD6ckgFdOyRJ7dTvD9Zhg31UKUgmNaP9HvfhDOc19uG8CMMZQGuYe6qS2qwPZ8lwenaosZ7hLJvUp30dGMPJJLX+LyhTatXBlFr4hTWvak8MGReTh89PKalN7OgQv1usA+BEN7q3DzKcTFIbiz+V91OtNZFyffS1TzGcg7XQwcM5BpwLmKL4ZcGykSXMOu9ziwynyYoEnqVmapawj5Y9g86alLwuFKxq0aKH6k5xDye+VdIBhpM/07GASInw7Rhwkr/XFKFRxlg0wkAL69lvKipRwfDI54mHBqEIqdNu8D16xQrazUhqQ1CKDO3YAPhng82BT53+FO6JK3CqTXJg/lyEecLNeDhJLXO0pDa2RfHFVPeggDO2RfEgLbWV8cc+VVQcjZqEsgTE3Bfv8rYosfgVGc6ah1NF5nFKUmsp7KsMDaK5Y4Gktm1Sj3V+LLS9UxYatDT0iTIkYtHlARjOdVNJYmej7Nk8N2JoUEipbXhKLerhRqI9wRr9KDQoWbceSWrfXoMktSWLFhYRbtjBGM9wjphK2eQezilJ7UTVKxqazRBfhjVJ7QljOC1viIy0aer/Q1WY2hisTX4SVqk2aoXGhpehc0B3Hzh/Lf/luFjS42bxtJ24kJ0AnCb1G0UTJLV9bTuJ4eyczhiY2rgQw3nIw1kuCmsezkxSy2SerFk0MO3hpN6napUznDKcG1trsQHgdD/gOz/4HL73I569tMMOe2isT7x8Dv05vvyZ6wCAq3sPONuJlFodJLXO+XCBMjRIwWIIhRbb77ENgNNYlzVap6o9BR6RxNRUwqX42PUWJ2IPVWGBSVKbGE6MGPToqwjjmOIDjVdO91kvVz6MRSzSfKX1rWBOWgXsQzJqYJAgxGQLH+n6POGajUE0CXCyczUV4w4koKCUClX2eo+vqUUw+cGEVBhEA+U4w9kHhlNMM5yD9Z7AADiVELEfKDHaI4BBDGdk/Y9L5ONAcl5SyxjO8ExqJWCchHC+2h5lgqZS5ACAEBrkCwltti0bAnI4eKndu7Sd9PckqX1ooUFw4K9wKpI5a5LkkklqR62HDgLOlFKbAoYqoUEVhpOKLP7/D7dFEWG+oGtbTd6cGiSpZc8MPQNRDWFzZi1ri8IYTpd5OAdYE9iewHBKODTdHc9wasnYqoniDg/Fo/dGH9QczaXR5+kaGlsCTq7iSH5gLVWUix81OGBSqZjqgufUSo1etGjcPMPpIIKHs8JwAnjq/GdwV1wBpE5tUcpCDNJ7t5ZSS8mvx6bUSuGf+7KNyUWHlCF8LG6vZDjVMhav2oezCABjidgezIyfc3q3TqXUKuEZzqnQIM9wcsDpC41Rjr9AUrtakbpgnHRuIWGsi/abxaFBggLecqXKeD8WMJyNOkBaUGjQ4X1zCHOE9fdSE+Xs1s8nlfOlWi+pHQNOIjb0I8D5thp0M08xnEPH0mZLwKnylNpRaNB8rPOm9Q+4Hbr4Qm8qsdonJwlwkhSVBjGcKso75vtwriqSWqs20PRi6bcAHHD+Grb7AbdD7DRNjkpp9E5Vg3xiQmQFmPsPdNErS8msfYXJsQXDeUhSK+0e36q/O8hGDwBONy+pTf64YhJjL+X4QuWhQbLGcJKHs74YoN6nZWiQ1go710RAWg5aYFMLD9fv0KHB5hIBzi2+6t3X8Uvecx1XCHAWDGcEJSosWFyoAguVWm2ExQdJJ+3QRYYTAE737JkJ1fEEOKnd0Dw7TT5W6i/HB1UlM0kthkxSW7ZcMM7ha+VP41fKD8Z7wViHv/kjn5m8Nz57NwH7UnZorI0y9C8zPw3Ay3TQ3fcfCAt6AOhF3SsibQ8r6i9FK3Rk7FzGNB72cMrIcOb7TAWOqcITJV46qTGgyTyI1gyx6DC1iO6NxVp0sLEtUArnoALSOKU23G+a+gaG///0DwE//XcnjzXf53BchaR2n0lqASU8U0/VuFZJllJr4yJaTbA3LniZVUVS6wha0UIZAmqRpHaIC4qy9VU2jggNkkU+QJLasYCcoJ6oMpy8t2ZlNA1nOKcTbWtJycqle54ApyuKDMYFFhI+XMN/V9inI1JqY8Ite2ZS2nhiOLkSIGuLonwvPAmbPYPOJhZcSBVbrKy72zgTJx5ckKR2qrgzHMtwMpaajUxuP/TsXqKCYX5uz/YDXjmdAYuwMaXWaQps2ib7kGg94JwNDfIMpxBMEUQezmvvBoSExoBTeQ2QetzSxR+Y/7U4p/HQIGI4w58X6sM5Dvm56MhCg5AAOxUdeuikNJsbFDSV3Y8Fwxn7cI4ltZHh7KmF0PiZFCSpDQxnTVXh9z/IQYHk4bSHAGf6+WoVij2mwnA6v8+0TlnaFqVkOCdTatUShtOHBpENA9YCP/D/BLbeW+y9lwvnmqBodOF68NCgsihAg8iDMkwwV1fQOvER4Hzrj4mU2hguM+xgrPWR/CMQ0uSGaXq5hEk0JuVNVGjW2rdFsWaIIUW1WO2TDXsxFSloVPXL+3BOLxRrklqn12jpgaSFtO3xZ/7Bj+Fb/sqPhH+HF4IObVoqFVVDMqYJDyeGIVblCHDWPH4uejh9D9LJUI4wvnj/0/hW/d34Kvnxg6FB8pCk1qQFRv6L0oPOrA/nREotTe6HerTRJFS0RdFSYIsV7ISklpjK10IxwA0dejTJC9qf48q6wd/+j78Mqj8DZIPWFT6C6CfTcTEunIEVEi54KOg+pt6rZuhx3qXrnrVGCQwnXVdqnzDV/4rGrh9wgj0aGPSlx4zYDiapbTFkz6FvKp/OrzEO/4n6+/g9+rvQhXvhxz5zG7//7/wUfvTnCpl4GC/cScxI2Z7FJ2n673+neQGP4zY2jQb29/wHVglwDqKtekWkq6gjaPtCRw+gswP2LrBCA7F4Fp95LS88UEFGKQoNKu6voodqOQZjQv9FjUHkz5ezAwaS1E78fhc8nCSpFRKx8h9BTDEHlW0cYjX3R/4C8E//SPV7+OAptWompTb2X2QSd61S6i5P3ZwsZFkOOPPQoNgCJD4bKyg3jBb8fjOcyUkqljkwReznEkktgGp6pbVMctlsYIWutkWhnILp0KCUgEqfHb0D/RePQ4PcAEOfDe+kEcFqUhCUGIUGXUBSy9lJej/pdAxZsjDSOcoYzhJwMraHAohO+texlWGuDb6+GqD2x8jeXQSIo4ezwnCS5LxYj3CPnDWJLVdKRUsEH3/2ez+O3/JXfni0/fg9XGKqSVGzg3WIaq5BtGhmJbXcw8lCboa9nxdvvBcAcF9eg5CKMZyc2SOGs/B4s/2igsixAbNKInoSH4qHk/XhFM6l7YVj95La5QxnGRqUgcoYwmRG7CcVJWJv3AlJLYUGVddkQCoqMgmsDRJkflzl4Me4XlWUTIwxBYDbZ4FMWdwWxQcBuoGBsspIktpphnOtFXrHgvFe+Qjw/X8U+NnvBeDnATtxnOVwAcSTpLaNklrjxcgTDCcwVixRwZVLaufakL1VxiPAKSdCg+hFYzqWUjtOX/WAkzychaTW+h5eUw/MuvXVSWtSJbVpxw/PlQ1jNXUOTghoxuqRVF4CVHn59cZiRZJa5j90eo0Vwr4T4ATw2c8+m6qkrG9jzytGbESpXlkFJ0ktYzhVqO7WJLUUkS5jqMk8S6bDgr3FcATDecjDWXk09Dp4OKnaz721lT6clXCA7LviwiO/po2S2KGFm5DUkjzjdgScex/QEdNtw+/dfc7/efMLsHI79EPaD6qwKS0jOyVC1TZ5FUIv2gAs7NBFSS1QBAeF7xQB9Oq24u2ojG6/hxZ2HK0ORBlMznAWhR/h2wjQ/T5Yn8S8xj6eJ2JlqednOV5gDGd5/wzWg1y79i1nfon8aJDUhueEJLXwgLPG/Cs3TEpqndARULsgZ927Jlav//5PvYBv/lM/gLtbHmZCLJD2AKiQMx5MqaWFudQwQmcMnTUDjPPz0nThymGNPazy9xsxnMIZJqktPZy0eCDASXPmsCiN2c8t/nfIM9lXJLXkm+fV5kaRFM6z6TSmmEnv3RNeNRI9nIWk1iXA2WAYy1WRCgPhH3FxPReIIyhtfIGk1l8fznCy0KDwzCipYNQ6MJxlQWee4WyZpDYqgGqS2so9qN0Qfe1+8WtGDGvWW5UktQSCj5LUhn3K+smSBYSCj3IPpwwgBAiSxMBeIAOcJvl8g6QWAFZ2mwAnfNFLw4wANVBIDQlwdkFSW2M4Y8/qeps2/3+pwKGCP7m8X1673+H1szmwyJRXBDj7HSypuVSDTq6mJbXOc/02eDhjOx8EwKlXwGNfDAA409eBELh0UFJbSakle8axHk4pCg/nAyTU8u0RY5pSapOkdpHst8polUm0FCTjMjba70j4vm46YEtIHQBnSjQvhxV+TuQA0ToJd5DhTMe4qUlqw71JgDwynAtDg1zYLyrWTM2XSVI7zXBKKTDIForey/Tetv4Zmus3WtsvCg3yHk7hA7sCVrA1D2e5JqNR7cP5CHC+9cdERTEap82+KuUDAMgGCiYteGghF3tLpUj12lhr7+F0posAt6nEzl89adC5AF4qbBiQgKeLlcYxAzkYh40khpM9pM0JVlTJpJchgO2dl+MCnLMqvFk9HzYEC40ZztB82/Sp3+jKH0fZjobvu1Be8jfZWD0Mql41GB5eH85a1V8HhrMiqXXVtijzgRIiMpz5wqNREjvXJEBaDDpGWlAI06GXbQVwPuv/fOyL/J9cchY9nBqUViedySS1VN0nSa0rJLU5w0mA0x+Lot54BxjOfue9kFqMASeipDY8Ty4sUFlBwzHpEZBUBWuRmi0T0JyU1HKGs5QduiAxe+qrsBdr/BL5US+pjR7OxHBaWZd/K9dHOV45PMNJc03nASd0lAe+fG+Pzljc2+YLTiCk1FbbohyQ1MawCc9iqKIP5xAWHn5b422QpJaCv1RciLlUUJpgOCGVl1rRv+2QJIYzwzoHReDEJvYXKBnOsc/XS2oVhPXeUxpz7Ux8nzXm4YwLai9fpPnPqDVaDFXveKaacSZ5uWci+JMP88DiIzaKr7dFyUJlAuAcMZzRwzmdot5D+WsUfesVSa2YkNRSMTcs1KwbP1sUGkTFO7q2c71KRyNKQiuSWioKlpJaMAAqVWQ4NQafUYCgdiHFi1CZKmivUqGJJMPl8fltzDGctZRaYk0KSS3zghrTM4Yz9OIt7pfB2moRhG0xMWpR9ucT+VsMcEJjkCv/LNW8zlE2KSHAvMfW+HekXsf3znlzDUIFDyfvwekPzP9e9KWPGU4KUjxWUqulfLiSWilgnfDPP9sehQYNWMjKRzDJJbWuYDjZe435bQEmux5mnhXpnznTT8tSvXQ19XQlhjOFBh1mODeB4SznOto+kNYpi+TGcb9YsWdCEbJaEBoE+PdyLC52HHD699Ti+0LkHs6Wij00j9bOV7iHS/IgK8AGlcQjSe3bYUwwnPGhG/aMWcknFCE1WmErHs4yNKg+EW1a5U3tJrUTaCpA5+q6iS9Boujj7hPDSVUnwRYdxeiNw1rSQ5y+RzZr3yuoHzLAac9fi8dGTJVvi1KXuRrrmcNRNS16OPs4MengLaqlcSZwq9DLZjoFMgyaTJqJhV/2WcyzP5OSWoAxnLT4YoCTezhHbVGOlNQqgR1Wkym1dIwJcO5hResXTmqVFjTEcIYXv+RJxIyxNpA+ac3ZIKn1Ez5VLSPDaXqcM5bwNGM4cz9q9OodAJxm53+vwTCS1BLgVIzhbFgzd4BVFcM5ptYpa+bn3Yfz1U3IrV+8t43BA0OF4WwwQLQn+PTmSxPDWfFwWtVGuScf2lWKVfQ7sonH54zv1+lDufx2tuF87yv+W6WbGNbDh4iS2vo9bhnQ8Axnuo4ueDijLLxy7/q2KF0MMBMCoKRMep7HHs6wLyIx6v7nQwpRmRkxMApJ0VBtixIlten5TZLaAWuR7sepQpYLoUGSGE4eCIYgfQrHY9Ta37uVYkaWgsuCXuYSEReHBpV9+8C84yygCFLDqpVvizJR0FETDOeq8e8nLwc+JKktGc4+pUlLBQU3AmQDb2FDskk3z2pUB4HKImHW/19oqWFtNg9zhlMIGReTGgZ7BE+oHaLaRkgVPcsA0OkccEa5aDEyqSGtD6KHcyypldGKUG/TBvhnlO4PrVWUs/MxWDe+3vx7GIgh/6zrdyyvovUWAaDenosKfLWUWtP56xkYzn1zHZAaUrgsQTkcTLa9UUqt1GhDb8ujQ4OC1L/ay/ICw0t0xwwnxJGAM2Y7lJLaMYsJCqTJPJwhyTh6OMfHRQwnKU5qz1O0YxR9OFNoUP18E+CUgnk4eTgWA7BAYjgXyY0BVvAO98Qkw+m3PyepBQAnGWlB61vTwzqvQKx5L6vbofCz0HOz1TID6NXthGKOK56hKCEP97QNBdu3+ngEOGkhWABOYs2k3UdJ7djDWQDOMqWWfEdTktpG+p6Wtp/191zbMMC5qjOc1I8TUVY1rkr2xjLAmV6eBBLOzu5nktob7jQFr7DQiEHUGU5j/Qt7LKkNL32WUtsQ4KxILlNktIYR7WS4R9x/xnDOSWqdc3FxPRljz4DYaJQMJwecWR9OSqmVwfNV/y45TDGcAju0wERSKS2wb593cM5B2i71Ums2OcOpWuD6u/33McBJbSoaLaPPRcLCQaWKfXgmTJTU9thOejj9d8bE3dhu6ADgDBKXmqSW2I4ccOYeTscX2fAsfgMvnSSAuSeGc6IY8dk7O7z7pr8GpQfYUu9a1eLTl74CXyI+jatyN8FwtuNCjDX+JTUlqZWJ4YT1klqfduu3Q+wslwPzJunVkLBwLqYYzsiWSO3lRo4v1H0fTlV6Ldnwkto+yvtjWxSbPJyTDKdgrAPtqx2SOmRiGJtSamnx0NUktZWAt0alCvKGMZx6JuzHt0WRfsEgOeCUABJLY9QajagrK1zh4YyL65kFjljq4YxBH2Pmw1qbvktKGL05wHDW782VDu8nMySWq/JZV0k0Vs4kGXmYT0Yth4yDKhhOdZHQINonfg+RZC32Ep3xcErlQ1aET3HvBQHOxLI4KbPz1DfsuQ+S4dp6kd5vg1wl4BZ89bVzmQp1+b3JF/TWDL4liROs12T+jhmMHQWg8cFlmjEVvd/BGe/5c0pHZUsVcDKQImSSgvu2KMRwvh8A0LU34prADkO+r2EfCVDnktoNoFYZwDlm+DYmKVX2QduiSNaHM/NVEsMpljKcY8A5Dg0iab0FCkltyXCqah9O/17oh1QwKUcMnOOSWoi0/jogqb280pF9zt7zhYczMpwLPZxOhD6ccT/mPZxzkloAcGqViqoEOO0A6xBCPY+R1Dr/noNAq/z6LpJVMwzn6Bmy6R0MALX2Zm/F8Qhw0kuxlMJRaprpUg+4kaRWo5HMwxkBZwBpIURnqlq7aXxoEOzg2Q2nqlWlq5vGS5sA6ILhTB7OvNqWVZzCGKzFWowXDgQ4t+enGcN5Q5yiNw7WutT7TyoYNBMeTtSbDCtqD9LHh1OvZwBnWGxJpTCIFvoAwxk9nGIecPKkyyn2B1xmNfqiguHkPljeh5MdvxVqzPaEkQBnWUSQ2LkWovaiRwJOvXG4vx8gTQ9Lks3mJGc4rz4dAS3vtWpZaJCXOJLPRbIKYwCcITTImUJSW2E4Vbiuk2FcxbDhfmt4+BYNQ/LMFBo0eg4j4GSyWwxeUjvk7OCU3PqFu1u860bwFI9SaoFGGEjd4uUrH4ASDo9vf27cFgXwveZsl6ftmlSoqQ3HGEZhPNjrnI7+1cRwcv9tAJQTKbU4wHCajOFsoDOG08BwwFlJS+2NxUbso6RWiiSDMhNtUeLLNLRQiftM2z/AcsZ+iEiKhqqktlLka5TEAAkBc5SkVkoAv+i3Ar/6z6T/oko03W+R4TwUGmQYy/sQPJw1hjMCTraoFwpO1z2cUbJeSUYHPOA0kLB2SKEb1bYo0vuo2dCsjRgFmJRfHwu5QAqIiYDziNCgInAIYIolnSS1sUggdAj5IQ9nIakloGWHWDQQUmXHPjSc4axLhv0mwr2qTxIg7s6r/k0gMZzjTIl0P1jTp9YMoZhS9uE01lUZVxqCASapW1gnYPttfH6dbA4AzpzhlBRyY51/R6oWeOYX4/8lfwt+9uY3JlaOyYH5dujmyEITv/o/Bn71n2KA88iUWpYqm/UdveBIfThtAOx5aJBZmnZK8vzCw5l5TJnsll8rAFF9kqwRle8VPl9kIMBZAaW2YDj9USWJ6FQ7P7oeV9ZNfE6zVGVWjACAO+eBEDgqpdYmtdnEXED7cePSAYZTtf59ZAYmqU09dt3S+0Jqn4DuKDQol9RWu1HEHrdlaBBJasNzIwTwKDTobTAIDJU+BWK6bJfCDSpS0VlJLb0kZvpwGqog22EyLYtLapt1/qIiI32Um8x4gLqBS2rTy5Pkrdvz8wxw3hR+Ud0z5sKzjip6IflIqbzFgxdlTUlSS6FBNY+fZQyn7xM4D1poXxoM6IfplyyXcHnzd8VzM9crjxjOWh9O9nnJpCNWqEm/qDIEOHNpVaMktmgnw1Q4cHr9rINyXUxQzBjOO88C19+VvDCZpJY8nCqm1Cr4dhK+35SJLzQTjtOZfhJwuv4c1gmsiIFnvVfnht37+01XQkVo8UnXP/bEzDycufSTX2OSJO8jQK/7EV8+3eOZm6FNzyil1ocQCb3CvUvvAwDc3H3av7iEzNhpp1ZoxRBBoj/A6YW6/50meTjtgN6pIKn19xgxm/ueg6rEzPjqbHHeYg/VcasZIDGcQjWwMg8NopRa6jFWldQOFit0US7E2w9QoUsVCoLEcKoxwwkc9HEOLKWWmtFXJbXU8kVwhtMDJ+VMJqnVGM89dMwGyjOcj30R8It+C/vPkFJL6Zp6hRamyp67IjQogu4Zuaicmb/zjSfGOO5ZWFQ63hZFKli1xgY1SS2pOaYYTl8QNcOQCidVe8iY4fSAM4AnCg2qtEWJDOcDSWrp/cL6ycbQIGqL4mKRw4jG+9Vtej+LADgbDDDkWWf9TIXUaY4FYBjD6YSuHh8AphI5yRnOSkItwK5FUQzhabckqbUQUJIUKvnz1huH3rjqOw7wQIaYHa0k9mjg+n1kqjLAWVPaMJAigLTGcSaEBnllwF+0vxZYX2fpu4WktvBwZsXqJz4AfOVvikzW8ZLaHHA+HIazIqklxnEpw4kA1EceTh4aRPOvi4XguB+kgiA1yYSkVsJiGEz8dzkslH9u2bV0TmTJzLVBQM8znEECzt/zsQ+nPz/EcKrFfTh9Sm1aB9b3o13o4XQ8VIwxnC4wnMeGBpE8u5TUVhnhQCaUfUCJVIlBbxjbEt6K4xHglPUJPja+t/uqlM//rvYSnKItCjEQtqDNy7FulK+8h8j8qQrZtU2D3k0ATpV7OGkBbitG/4zhZOycXvuHYre9Hx9IIzRuIABO4zCYHATKCggkJnjKwyldH6VClN5lK0ysYx5Oq1q/0JzpS6exLDTIt4VJ7E+tAjwvqV3nfTj5Qo0fM2c4MQM4aQEySqn1ktophpMzOq+fdV5iSOC3OclTaq+9K4Ki1qVefLTYUlpnCxYnVAxBoBAOE9JInemx7Qyk8EEsp0xSa7pzbNHiZEW+rWUeTrrfNIYRu0gBPMQQmxDgIzIpcx5uYzlrEs4Dgbaav/elezs4hyipHbVFcUlSe37pXeicwvWzT3mGs72SKxJ0ixV6nDHZMRibWBtOMobR9rDC954lwEmpwDvOcJo0rziIkR85XlvUg0MMSy40os2lpXaAgUr3f+W5o7YoJKkVUWrmYCMrbXOwyzycrgY4DyTVEpAEEBUPdUktfLgQAyyxnQGQp9QeYDhrlqPIcFIwxqyH83hJLTVxvxDgpMULA8SQGk5vsBbjPpz0zpv2cHowY03PCicVSW3h4bTWock8nCHApJTUcg9nmL8adwGGk1k20k6QpDa1RaHQJiubIKkNfTgDwynh3w9WNl71kbVFUdm8Y1dXs+NXcNWQyYzhNEsYzroyJEupNUNk7BoZEphHyoyQFDqxhhVwkVFrtQectt/F+drJJgJvkBInOzACFcHDSQE6zgbA6c/VrjfYNCq+D8zQFYAz93DW2sK1F2Q4NZcbP6zQoChDZQBRHA84qfVHHFN9OGN6fEXJEN7Ps6FBVFSqrEFj4BxjJA1kYvUn5ilaa15eJ0mtq7RFMeH8UAF2aWgQeUsPMZxPXl3jyasrrJsDxakIOLsccMKFtihL+3CqCDgdBBqVA84qsUTqi/IZcvl1cUUB4q06HgHO2LIjBz4kIVK2Ty/GcjJUGg3sqC0KLfjsjH4eSB5OCnkwE5fj6kZHhnM1yXDmk18tpbY3Fq1ICxEa7dpXW/fnycP5mn4yMZyDZdIiHZrV1xlOVev5JJX3erAQBlqs1jx+sbKl/IIYQJawWg5iiA55OAfj5ZaAXxDXKtLxvFUltQXDOSmpTb9rhZ70i0aGk2QX9DWhLcqkpJYd4+3zzi/SNGc4zz3QOX0BuPZMZKI2oouLc2KctFJ+0RCOyQkZQRy15jA6l9TebA1urizOGMNpdmfYYuUXF8BihpOYrVaMWSJiLOiaWVIaZEC/8HBmDKc/f3smQS7Hi3f9Z56+voEQY0kthQZBtWibFp9y78Dl00/4eHUmpwUAoVdoMeB8z5mtxCbWhpM6Hp+wQwCcOsoDt9HDyfaLA85KQii9uLSwMY04G8wvZaXvJZy8VAMMJBryUlVW0YNx2GAPwdndACJtCJrSwmYSzszDKVjISWQ4l0hqieEMoUHhuu5HHs7xHETP52WkZ2pSORFCg+r97SQAG8GLazaTha6Rh5Pm+LmFMy0mDyYWjj2cUZ5lTPLYCwU09ZTaKKmtLPKB5OE0w5Dm+6nQIMay96FvdQzKkgpK5IoS57zkU4pwnGEupT7RR4ELap/B5ewF4BSFpJYauAOeCRMsNMjJBkNQfSSfp8xSybHmgFNBC1OX1BLDqTnDeV5NqAUYw1kUjDlb7kwfAYqSnpUqGU6ax6Z8nJJJCbX0gBPDLhaMoBoMVMSsvXs5wylSoQTW+nWQXqM3fm20aVIBy/HCiz+Y8HvThd5147e9NHQmHmOQ73up4nKv3tSISg4UIJDkwkcATifKbIeS4UyMcclwkpIh9jzW47WKVBpKuCS7rUhqHQPPAEYezmUMZ6VAwtqicFZ66fVzobd2DA2aAIS//Ze+D//ov/h3Dm6Pevxi6EYeTnVEaBB50Z21sC55OGkerUpzdZ3hpHMUVSkQKJVKb8XxCHCylh180AtbR4azJqn1DGdXMJy+emoZwzlheo5x/UFSO3E5rqyTh3O1yRe59EBHtQKPxi9Gb5zvw6lW2aKnCYCz2wVJrZB4wd3CTXEv/J5lE5f3ffFkSxrR61qeJyH8S94mhpNAkK20kYgMjdIwkskhJoaKfTgrPsDs+H0oBIBqX7iwQwAOMJwHU2pzyedU5UrbHTqxGlXGGimwc824KhYGX2C/er9Dgx6SJlWS1N75DADnGc4w6a3RxXvVRc+MT6mlAosTKk6cVEG1ITQIZsC2H/AX5f8D/zfxVzNJrdmfYYfWJ7gCyQx/CHAyZmso2O4kqQ0LxfAccvA2lVILpKoi+R9r98ZnA+B86voGjZTjtiihTQBUi1Uj8Qn3FDb3Pgns72WBQQABzlx2nBZSEz6T0FoJAITrYaXGHqm9CgHN3MPJpJm1tijsfjOVecAwwGpFofAgdk9PM5xD73unijYVSgxF2bPrnX03A5w5w0ls9BKGMwDOoGigxTQ/N9GXUyaKh0XFiUiAc9IbHkKDan3/HLz8Le633qARdQ8n7/sIO/jzc+CVG9mKWiuKfOP+Tx5eGeW4yZcFqeD0BivUGM7DklrqEy1s7xfbVb9YHlzVGyrSFKFBDJDRvhBrTaCRCqJTrEZ1BKa/FX2c31LRkgBnSqm1svEMPCuiQunAcHrvqYVP5zWxd6rOC4yra/HvNnhCqwVM6tHXXPLXxAz+HVtJqKVjAZCl0gKIASqAZzgdMZxBLj5KqQ3342RSLQMxWgnsXQPX71IBmDOctbR0xmIJwQANMZxqFZUlm1YtCA2alpt/0xc/gf/m134ZvvjJy6P/mxuKsb+jUJ4LjNiHkyW6A4iKILs0pRYkoUzXbCT5ZUm2ArnPMIJ3KhjVFHS0T/00C+q917mH07GUWjFR9CHGmTOcturhlDFBVojlkmgCwukZng4NunFpXk4LID23Zp+1RfEptRZLYZCTiklqBTT1d2ZJ1qMR1rlZhwCk+53eS7b2Hn8LjkeAM1RsRbn4IJbA9ZE1EaUPSzbQwiZmhoMiZ9iDW39ghBBwUnv5gDUwE59TUsSF4bpgOFMfTmI4KaW2BjgtVqIf+clWGwKcZ+FleBkvDpdwS/iHszPp5Qypgi+xwnCS7K3W8yksrKMXhRjOysKKJ/bGpMMZhlNnKbXTVaK+8HAeDzhZSq1sMtBOC1zrRJawaKWa9NI1BDjLr1ESO6xGk1Q8DnaMz9/eokUP0XBJ7Tnw7I/6fz/91VGyuwJnOEnCROwzA5zEkvcEOIPk13Q42xs8hVfx5e5jmaTWdufYupXvUQmke+yApFYOHHDmn42AswgNEjOhQVH+DgY4A2irSWpfuOM/885ra2glxm1RjPFFCtVi3Sh8wj2F9t6nge1toM0XQFKvA+AcS2qnWCSoJjKcMjCcA3Rkd2sMZ2LhQw/V0sPJnv2h9nzRPqkGRhXPlx0wOBUZzppSwoSeYoJJwSPDya7hwGRWjklqSX4LANt90SpiYljrIIPfr4kezrGkNiaDF2yDC8/zJaTFMwHXcggC3RXPUZlS67Tvw3m4LYpf2E2pWOJ3VwNFKqMiqU0ptYnNg5CA3mAjKgxnuMdmU2qdgjU9hB1goKvsrCsYzsF43zNYSm053xI4KyW1LS4gqRUCRrZoMaQ0Z5Lj1UKDpA8RIfZfCBkZzkb4+cW308h7dfL3v8gYTgmNOsNpOMMJ+PfHDMM5lZrPLT/ODFHWR6xbmXBJ13qqFycHMY0SvhWM2ceCsFM6hsVVQ4NCgWiLFaQQECNJ7SrOXetGxSKsM30hqQ1/d2lOK8emVfitX/feSQA0NTJGsmw7coFBAJZ8jwQQaX1nJqxTtWEj8+pHyWJmklqXBwrF5zz2Lq17OP1nuuzffJSSWgoNmpWIIklqr6x0LFZl1pnYh1PEBNmlgUF+v1RcEwNHzgWVQUFcJcPpLCDFEcw3Fdac930qkZ+v6nYoDK1Yv0brFhUJ6b3yFh+PACcxnCNJbZBpBt+bxjB+MUuVpWvyxtOwhoVzzDwwUkO4wcvpZlLOCHidXMoro2VKbZJVVTycxvkKcnEcq8BwDvtzoLsP25zgpeEybskAOAcb2QqpdN5Ilw1DzdlrBnWhfSAD9d2MHs7Koi/su1I6tfuYAZwESBoxZOxfOQZjM8BZUxvNtafJGE5dAEWS1UBm8e0OKjW8Ljdnd+jlevRz8nDKCVaXL7CfvX3uQ21CJS0ynJ/5l8D6GvD4B+K53rDelATQGkUMZ5o0o6Q2LDRsrBB69m6NPZ62n8XZjqXedlvv4WzDtY/hF/NMjWTMVtmTlQAnXTMCk5mHU+YMJ5fUkiR5juF89f4em0bhyrqBlmJUsIjKB93iK5+5Dnvzi/y5evGnRgynbH1o0NkxDKdq0LDQICuCR9rOtUVhyomKpJYvPmseae7hdKJY4AZJLXmpTGUesYHxkIylsWEhxhntWm82Yjipmnv3LADAAym1MZAMyefXsfRhkms6F1izcoETFoVcUtvMMJzWTTGcvJG8gNCrEFZWk9RymdkyH9ny0CC6TyuhQUwKCqnhmnpKbQzKmwKcTUipHQbPvk96nXI5WEde+fCcuhBgwr+ewGdsnxMWhVQsqsmZ54aVDVqk+T8u6Jiklu45K4jhTHJZCg2iFGxSHiUfmYpFo73TmbWFjq+W+UELcUsAc9jPejhTan7+3PHn2MtSE8tiIWObKxrE/k8l1UqXetWSpFYMOzim3knv3grgDAWirVuFPpwkqR08ONYr7Dq/D5uGMZymYDiJQTbpfn1YgzOSYIzkRUeeepsksPQOMmJijq8MJwoPJ9yMh9PBsbVhZPxIUVcp8NM6UIR1UzWllnykjJH0ktqcfSsHrTWvrHW6rtk1Tew3MZxLW6IAgXl1/Pk8IkCsMmLRyZSSWurDebyH00JCUmoxzTUzgHPUn5tSaomtFo88nHEIIZ4UQnwo/P1/EkL8SyHEH3hjd+1zNOQ84NSuhyHv46i/ZAMtUluUrLkr9yvOPTBS++9yZta8TAEMm5PCNyYEpEjhQY5XuYvRUeW5AEu0zX53Duzvo1cnuI0ruOJOIYNHlVfK7ISkNvbKqwFO2aCBSawHNcStLPqSt0andh8V6S0NCl1ZH2iL0huXhQZV/S3Rs3MgpbZgiR0DnFw64qSCEnX5bmv36FUNcPq2KNL2VWkdHWOrJZ573TOcOgLOEBr0mR8G3vW1fiEQJr0183DS6kgF2Rz1vERogu6/qGA4rZfUrrFHgx6Xtp9NO9WdY4sVk9ROVOqLIZlsuPTzUr9Fur4+NMik3nrABMNZAM4+AZNy9MbFtLtGydE9EUGDavGV77qO3/0f/e/8v3d3Rh5O1ayxQo9znt4b7ls5EcwC2fikTmsh3QBDoVzEcAbwmhVSeMuLihSHA05TAfy8j+fo+QrsXhOarQ81IBUWm6otGU6XS2pZMYkntBLrACS/6SGGMzKXYB5OKvS5xOSk3selpNbfJ1xSqyYYTs9EiqoEjHpOkjxW6HbawzmS1B5OyoyLqwswnEIQK808nFJB6LqHM6a6TvSIpZRaZ3tIO0x61GiBSCN65WmOlHJUdBtKwEmhQaROOJLVsLJFiz4VZmhBR8+dM7mklvmbpdS+DydsKCy3nuF0Nr0PhIrz6ClO8qASEY6vFkIXJbVhrjD72ZTaVAAvGU4+pyQ/cAwuKRnOKKmt30cCiTXTSgQP5z6X1NK7qZZSGwpE51hBMg9nVOXoFV657/9+bdMkJmyUUkvXa8Fa6cihpIB1MhaIHjilVgYmyjmAnT+aW+xRoUFFSu2kh9OO2E/J2WKg2oczsaDh/VN5nqL/nwoxLgDqAym1Qgj8xl/8DP6dL348zh15cY0AbGI4lwYG+f3y6bmpH/uD3ROyqUtqHUK3gqXMeShK0fVIPXBDsb4qqfXvSGXLPpxhfooMpzg8578FxtKSz38PYCOE+A8AKOfc1wN4SgjxRW/crn2OBrVFKRg7koy26FjfunFKrUbycGayAjskyc5c1U5qP/FYM8tw0ovo5GT8olJSJIZTsCp3MQZjsRLDqKJNklrbeQ/nTqzxursCCYdruI/e2Fhh9TJXfTTgdDIwnLQIDZJaV0upzSS1M8EFYdACdC3r7Qni8Vsb5YtTrCNNHkrXACdLqZ1lOBngpB50le9q3S7JlvjXKOHbogDVhEACjU9eXeG5106hhYVqw/60J8DZy8CrHwPe83X+Z03ycKZFOnk4fWhQVVIbGU4yvnswtXL+Wjy2/XTaqeEcO9cySW3di1QOZbiktnwGSVIb5IvOBwgJtkB2FcAZe62GxU/XD/h35Y+Otg8EX6/yxv9vFj8yAliSKpO0eH6MTXltznDqxktqOcM59AQ464t6mlOGfg/pPMNpZBPBNqXTZgwnk5+5mqT2AMNJMnapdB4ZDwDOYIBC0/j96isFA2o3IxjgpKRjNwE4ed9IB4mYEEr7eojhZCm1bfRwMlZtoEVT3UdOiwHOcOqJ0CACk1XAKTywps/IADiXeDixyMNJKbUHqt00n3CpnWIJt6wNDZoTbEQHU4IP+o4ZSa2BgjUDlOunGZwyNGgwaAWTvlfmQGM44BRxvmiJ4TwScDrVZgxnCg0KKZGFh9MzronhpMVkCwOpU2iQZYteKhqduk1ScgBwwcNZm+Njj77IcO4OMJz1edOWAVTOxVCWqofzgKRWOhtZs0ZJ7F0DMezT/qo2Ac5alkCXJLVCiLhwjgVEvcaHP+szIL70qavxXsgktYL53w4k+l9k8HZNo7YjD7A94XKJbgzxOSo0qFCmlGCjYDjz55zeeeThrDCc0SoxDzhlIal1kPHem7KCAcCf+A1fiW/8osfT/VrxcFoncX3j9+OYwCdi+xxT1T3IUFSMzyS1Jnk4j2A4SVLrIEKbnKQOqzLCqvVKhLItSiRVmIcTjwAnhBC/HMAZgBcB/DIA3xn+6/sAfMPE7/ynQogPCiE++MorrzykXX2DBrXsKBnOcEO0ro8P4EgWFwBnXMT33MOZTM9yRh4klAecwg3z8cxhYdiuxy8qJUWSf/Hm38VIYQ4520JeLNNtge4MZ1jjtvOL6ZviFJ1JklqhNJycCA2a6sMJz9BqkXo7zjKczDczWhCX30mhLgBWYj40yFfew4Mu5iW1hxnO8b0AjAGn/f+z9+fBtm3rfRD2G82cc+3mNPfc/r5O0pOfuif0JKu1AAuwsS1sDGWJxmBjKFOGQBKSSlEkKaACIQYCxIFAgBAglWDTJCEhtgOmiMF2lTHY2JIlYXVW+57ee7c9Z5+991pzjiZ/jO8b3RxzrbnW3lfWuzqj6tY95+y155rtmOP3/ZpP6MXqd+93MA2GU8uQUgugWV3mAscbDzd4/3mo2HW8+O/OElv1yRJwnmGcLcik1HAQ8f4PbVHK0CDPKbpuwjTuIivxxpQAp5huS4aTrps8ADh15lOdM5wsqSWWwBoo4QuGM/boKoKFaNFK2/7Y9Y/gX+//AD7+9M/Pvt9YH/ot/vgfxT9n/rd4cvMz1QcSwwkgyGgfvJX+nB9LH/x8t5mHk/vMLvnkeLvTNEJ6Ay+6EMpFx347cjBOznBmi7MqsAVA8eJqSWLz5FxXMdGC2qL0lHxophbg3NKuZwwnMa25RD6fg2JCqZAFwxmLCasYzvA7HSZ47wtpeQ44W0UvXhBfiLR47mGa3uoYGtRkOEMLEEFtrITqKWG5ARArJke4w4AzVrwPyauabVFSQnnOKLPc3k3lHBpZtIVFfmA4Q5sE4UzRa7jckIDMASdL41nOSuyha3g4IxtN2+7F4Xdma3jZoRPJwxm9x/zcOgfBrZNkT5aKxDJIGVI9meFkb5bPPsNs6RXOcdan/WMPZ7N+mYcGAWHRu8bDWb2/8wKEix5OiU5KuifL+8VmjH9r5G1RtAwMp8g8nEJ2++0smYcTQPRXCpMKdD/6+Wd4ctHjzUebCBp438NnhsSGNe7nu44cjAvY9UzWwoh9OMEyV9oeM5xHejhzVcCSh1M4G8BXHhq0guGMXnB+/7TWZFBVaFCYm0VcA604X3HOmRcXHUQM9TlOUktpsBGU3Y3h1MRw2mm3IKldec9Rq5nAbs8ZznagmoARfSwgx+HSehoAtUX5VQ44hRA9gH8CwD9G/3QB4PP052cAXm/9nvf+3/Tef7v3/ttfffXV+9rXD2cseDh5Ad5hilH/89CgEnAWoMgZwKyo2hF4E87uvfGjJE+fzX6mZbY42sNwhj6UJsqX4mDwNwYP55UbcNs/BgC8hCtqi5JAd2ilcCzDGTw2kQVmhrMlucwkg+5A+Az3ZgSAQZjYm6818j6caklSy/1Xl1Jq7S6m8JXHx4BTFf37uOl5/VXeewx+F3tc5qNXGeDcw3C+9nAT/WyaE0N5IaMG4K1vTfuNIKmtGU4pJUlq6ToImfwi3JONfl+4KbDgND5mfjH+WZht8HCSFHOpv209OpuOz1bghn3Csc2JnT+HsarMbVE45AcJcHZTqLRr83z2/ZN14WX4LMiDtS0/E2WH+bP/6mfC/ytJrR426ITF9S4dh5mSX7I1mPmcxh2UDwmZVvbx2FseTuQFmYakNg/0aqVVJ7VCB68yfwtCoc1AoqP9Mi0gRYtNPeQezsAk5M+zWfRwpn1mNtZs59em2OesLUqPEGmfF5e4CGMdQkpx9fKPgBM7WH0Rt9NSOQjn9gBOltQGTxjPy6axKC8ZTlskWy6N1X04uS1KIzTIZ6wFhIwFmnqujYBzr4dTwTsb2feFvS6KHGZi31gVGtRIqVUcMkfvrSipPXaRqYKkNhZmfAk4BfLQIO7DmS2sadHew0DpLrQr8zbJ+pSGooXrlT/HWZcxnFIvh9BFhpMB5214fg6k1M7bouRBZMnDGUDVXI7Hz8ZSATZveN8piR16CJt5OHWX0slbKbW0cN8KCkVpMJw/8oWn+Ka3HgYGVGVMWGyN1qdr4Ew453cEhflQ5OEUxHDuVZCt2V7RhzMDiPzcLUjTW4N7TfIoAGy2zQhu8+ecVXn7ACd9hq0ZrUyK0Jol93BWqatrgFirjQ+3BRQSj4jh1McUkLh4mSlx7jJY/TWO2ySptRO8Z0ntWsCpoYSjnsMy3V8HzpcRPfSCh1PmktoXoUH4xwD8q977D+jvzwHwCvlyxe//yh80wcsKQPGibcAUK7YtSa2CxWToRjEl4HRVFaP59Yr6NB7wcH7164+DfLCxLSmyClLWi60exnET++o4CKT4KTCcH5gem4evAcgZzvTiDSEJWWsAGtZxxXqB4YSFsyGUpDlR8WfziHS9n+G0zqMT6xjOyaaWGUuhQSEKX0C2qnsso91dNSS1FLJSS2plCA1q9Xc8wwin25LarWeGswE4SQb6ykWPgQOThiw0CAjptLyPQsCqoUipTQwn9eEkgOMJxABJUutZUutMwUR9FT4ftyfNbZlSywuQA6FBvcs8nJVPl0FXxym/LPXJ7t84yXNfxAzgcuiSmp7HfazH5HyIeX/+JfpMuQ+i0QIHrzDgnEtqAWC8nSfvqq7t4eRjGQlwOvItax9YvFZKbe7PC+xS7eFMf2+nQHOgik69Ejlcgpg7HT2cjYIBM5xD7uEM3qa6QX32pbRzkmSpxHDSPGu2hyS1KCS1xrmi5UPNcM4AvkwptYak0L2Y2iDB0zlYAJzwPspjJRV67NiYn5yF87SN2BZl/6I39Ss8sPhgj2L+u3kfTm9iz0++x+qANlGzgNUIfTgDw6n2AM46pdbG9yXNP9RyJD/XycNZMpwMOFfL3HgfqAdunVIbC8regfshe9lDZ5JaKXU8dxsxQnY9nJeB6YmgVEV5bmA4cw/nsm0iPgMMMG8/CP9fYjjpPNQezjwtOvw5AM5OcVJmOQccZDjrtijoIO0uAk4vO/jYv3CZ4dyC3juVh9OIDj/xpSt801uhfYyK/c4zSa3qYxGAlRX3OaSkQhhKz+WpgwEGvC/6cHJx5FgPZ16kEXWgWJTU8nelnzHA5Oe3Bch4/uP3V6t1is8komGf+Pj2eziLESXg+Vzv6TsVHmzCz49hOLnNkM/WKHcZ8b28vS09nJ4LL8eHBnkhwv3lDzCcACY5QC8wnHHOnoVIfTTHoTvqNwD4h4QQ/yWAzwH4bUgy2m8B8LMf1o79sg0hYIWC8qaYnPPm6eMuTK4zH5bqKoZzxOiTpyz3fyx+vQosaZDTLU9YF2dnRRuCfFwOGhfkKYmTX1NS65qSWtaZB3/JNd4dO1y8FMjrJ+IKk3WFnt4vBPl4ZwMQbfaF6sJ3O5IO82f2SWqFSkziEsOZSSj7A6FBIaWW5JawCx5OOwONcfD53z2bgfYYQz7zcOrmd+2Mwwa76I/Mh6aUWgBNwDkZh16FHlSDCOevHyqG85PfXfyO12fk4eQ0T5aKydDKJTKcKk2c3IeTIv2FM3GhMaoLfK34Aq63VGW1W9wiA5xCwAg9Uw7Uo3e5pLZmONlva8MC1c4ZmejhZPYiY0lZrquJRVUNwGmY4bwKgFNUrWjiwk83AGfdFoUYkO0uOyZefC9Uv3lOMdMYpFMipEBrP2GyPs5J7T6cmgIWlj2ctuXBzFKgI3jnz3kLCBkZ/lZbFW43oyoPp4AtQqL2pdTGCi8nEO/2M5y2Yjit88Wzvjvg4eR7+kJs4fUGVui4ndnx+T1zgAgL2OjzZIZzajGcBiNKKeFaDycaloVq48VxAVlh09vY2iV8hNmlqphywDc3kL8bjgDnEoMjZCGpjQxnlxhOXak82MMZF3wsqcURi918qAEDphgQllQACXDGno/ESOYLWn5vDpggKTQI3mY+TxV7HQcPZzrvXipoYdGuXdDzEAHn++XfZ8fRVlzlhVnvDGU+yIx1K4u/PM8vt0VJnkYtycOZS2pVDyHJy7rXw1kznGHu+/xzj8l6fNNbD8P2Yl9fE6/Nl24SUOFn7j4Ht63ghOK7ejilFHA+MaZzhvMYD2cNMCpATNsOditfPA9zD+f8uCIIjcq0FsNJ7w6Wt3MAlUtrg4NDlt8TNky/L2QCnEeEBoH7g0bC5o6AkxjOadw2PJwVs7xvcGgQqQPisxfX+QsMpxzQ+ZrhTDklALPNH32Gc+8T4r3/a/nPBDr/ZgB/UgjxFoDfAuC7F371K2oEn10AjoonzuyFb26uwh9aDKdPoUHCjrjFgB43oYISY52XTzPLA5Wb4PWeB1z1c1aNxr/9934HXr0kL0Wscs+Bl7EenZwAXVVXhcAoeghzC2+e48s7jVdffwP4OeAJrjCalD4pieEEECaZvBffnkqPVwFwKlCVf1/bjMLDyYCz3ZPSZB7OXthmr0UeU5ZgGiRQTRMnyWL3MJzbZ8DZS+XPeIFeS/HkfLEFBEbmTIy4agDOLvdwNo57NBb/qPy/4bH/PTFApd9kHk4g+TdpOLXBGUaMXPln6bAu26KElFrafwb5XZLUCnML9MDTR9+AV9/7s/j8B1/CS5efhHahLcpZlt5os/YeS6P3yx5OnXk4rfOJvcyfJ36x8mIye/FpArMd9fpUjb6mE3s4ieFUFZO+n+F8WG6M/ZgZ4IwezsXQIAIs4w7am8AskKT2JgOZu4LhzAoyYu79yCvnLUlt7kl3lUdaktKCAadtSWrpnhRZ0qYXIgSRLDCccUEsKKSKAIriQsFuP8PprIMWxHCK0Bs5T4aNDCen1FZVfwZjF9jC6UewMoT9NCW1BCZbiyRmJoI8VkHTnFD7I4FQGBjRYYMJ1k5huweAVAp9O1Dtjvud9lHF0CBL4JbeZXSNXUNSa6Cglxq8Ux9O7wyUF8sL6spHHJvNs5xVSijho2cSyD2cJKmlxVpkOI9kNUJa8A7PTDm/QdL85i0EAuD3tL/xHFNbFCAATqM7WKFmDKfSGtaLwHBm8xwzRS2GMyZYcnHq9r3w/4Xi8VJf8MLTa0PisfMiS6mtGc7wd7NgMZGwScYcGc4xSetVBykFdr6H3pNSuxWlh5MZzp97Gvb/sx+rGE5rABeu9bVVgY0PP7iz5LUeZWiQA9YCiz0jgExXsI5xzXWUpFYUgHMWahQLqYGZz8GoqooSek9KLUtqWwXP2IqDAwQV9XXmNl2rGM4ytI/3OXynxIPhhNAgqaB8KggdGyBWj45VKLfP0nqTPJxBUrvyvpNZaFDswyni+VpiSq0c0FeAMxX8WVIrY/H1ozxW3wXe++/z3j9DCA76rwH8dd77px/Wjv1yDi+oZUfBcGY+KKq+zxhOqaGypt/C7nDDEhOfYp2bPR15E/QwdX7cf+N/428HvusfaP7o6994iJcJcEY5ZAPIjdZhcLdNOc8kNqE6OV7juR/wyddehtPneIkZzhiAlCdbLsh+WgsTFc6xhg3x+q3KGG8nC7yIgTUtHwnCAjMynAsN2HkYZngBSHg0P0p9CJvsBu/L7lnJeAFxgcv9meKxCD3zLwGBsTrHNspV89FpmUlq52EqanqGvwf/H3zDu/+/FJg00DX91PcC3/y3AV9V5nl5vaG2KLQftCBRJKll+aoXSVIbZczs8TUjNjRxXj/5prB7X/pxwE5Q3mISmwJsO6Fn6c/12PhtZH3qBTG3reiFhXUOog7wQcZwOjPbBvsmOrsMOI2jlNrnXwYQnuF8JJ9bdr0//u3AN/8g8FXfW25McyU186XSPi+l1EYP4DRSK4nQe1bDYpt5QUsPZx4aJGbpdipbnDYltcxwag1UagVBSovIcDYktVGazOl/yCS1dbhJ/MB+htMfAJw22+6ACdb6tofTAwp+VuQTGcMJfRbbaLRCg4QPHs6WrD54wnwIeYOC6gnMTQ0FhrPYMcNppgh49g6ed05pixLlbTaCZiAVO+rEYuHJN7cwQkqtBKwJoThLChwhmpJayTJy7lOYXUMGRNJXoUEnSmqF7tGLnOFMwJU9w5LPSZTA5gxn+P4NSFJLIDUqe6RGpwT+Lfv9+E/td8wktXoxpZYW7zXDeWRoUOmRmxBSamUWjFMuVlNKbfs+KkKDKDNAuV0q6ukeSnC7lHYfTg+BkQCnJKWMIjXJT79vcTlofOoJqWN4/sv6cE7QKaTPWdh7DAwCAgh2MTToCK/e3o1SaJjPmDF+7o4BnBzYw5ut9y/OA56uVbrfpC7BZGt9KaLsltvczI+dCy8RcGpdhAatk9RmUum44bR+O0VSy2mw8d64I+Dsyfrhbt5L/5hLatcWtwS3RQmMM/fhFAeUjFYNMWsjbqqWCwsJ/CrwcB59Jb337yMl1X4khuPwH+NAoWtla4FdYDhbKbXKhz6V8B7CjrjxT0IhzZm44NrHcHL7jc5P8LLNYAIAPvM3hv8OjPhdC21RzsVz4Ozx7GeTHLCxVxDe4sZv8DWvXsKdPcGTHUtqk+9rUQ5rlwGnUD20eArNXtWF/qfh3xIbYjvyyY1XzeM1laR2f2hQSqldDHlgb1Zrrs0Zzio0iM+7rRrGR7lV9V2jcXiCsVnp1jJri9KoLjv6t4f2PfR4IxwP95p68tXA7/g/NfY99OLb8SI9l9Qik9RKhVgJjim1FPDkJmxEeIHtXv1m4KcA/86PA9N3hmOv/KhO6L0eTu89Nn6Lrb7Aub0q2woBxSRtTRY2kXs4Y9/CMlgIALoIOMMiSDcZTgedeThrc79sMZz9BfA7/q35AdHxj7s5a6sW+nDG0KBpJD9bF3tjbrep2FCk1OYFmYakViAHfS2Gk/3YXTouDmTyFk6quIgxjd9n2VweYMbhHLnMvgScKaU2Dzri5Fk/7gecefukHgZb55seTu/bfTjZw3SBW3i9gaMQsyVJ7bL8LkhqJQUAKZoTbEvy7yx2YHbRzpMom5tfGRqUtZnhEaWzDK5oW3zv1aFB0hmYPUuA4OFU8G4HDbm4oA7V+Yy9jCwZM5zz1gkMiOKCL6bUsrT/ODZK6iH04WSGM1s057JKS5aBnOGUUsYFuhQeSmeAkz2GUkJJid9v/i4AKBlOSW1RmoIZeq44YOvmgKSWMyX2eTht8nBqlXyF+eBnY8nDqbIAqy7zcCJKajUUWztagHO6wSQ3kI6YTRF4P/bN/+Q7O3zjmw9j0UZFb7KJ6+oxB5zkm773QQCRAfpdB4eGIQOIieE8ri2KnDGcuaSW2DPYGFLDg88lkyJaNxhOxd0XxvCrrQJO1Ral0wreJMbuGEmtaBQXpZR4sDk+NCgoBmxiOO/o4ewIcPoKcHJbFL/yvuO0bQGa+4XAVKvDGsOqDXq/g/c+KgF4spAZUfHCw/mrZHipoWEwZW8MldPbkeGsWa0uMJzGAXaCgI8x4dx3DTjAcNI2tZ/WU/t7RvJwtlJqPc7sFbB5PPuZlQMe2A8AANfY4NOvXsCdPcFLuMJoEsOpikXq3MNJBzXfMaWTpFZoQMroD5qNTFJrWba34PFy3sdU0h6H+3AmSa1tLzZdSOlU+xjO6Xrug6XFmIFCQYxwQmP1XbtxDD1RG5Xu7kBKLQOzi+ndKKldklunjZ7jDLt0fnjBr4LkTOayEL4PaaEhVZCYaVicgfxZr/4a3Poe6r2fjOyzqxJ3ndTBm7zgTdgZhzOxw06HokLt4dS5rH3aZW0csoVv1YczZ5rYN9E7SlWtmy8jPBO9dMDNO2HTlblf+gbgXBr0GZsznFm6c/NX6Pm3hiW1OgLq7Tbtb8FwRqZGACj9c0BYTPKoWWP6Mvpune4bkyS1QqhYCLMNwBl9rlmxxJHULAcVtuHrAQdvIHjqGHC2mPx8OLr2DhI9QthPS1LLfVhn1eaYUrsFurMAOMW0IKldTpNNyY4BlHKhx7WCVZzF6NnDOc2DQVqjKqAsjgbDqTjh1tpCoiijnLG+t00AYAtDKxl+7gw6Yfd6OAuGkwKU+N5mmXB+L9k6NKhKqT1eUjugg00MZyapdVTg4EKCF5I8nCkpMg8mUV0fiqLUyibsThkilQNOUFuUfQyn5569hxjOpYJxEcpiABdCa5QQsH65LUqrPyzAjBqdc/JwKm+SXF52UIIA50JK7Sg3qR0KAST2yf/4uwbf9LFkORCFpDYcy4gu/lk4cy+AsB4819wXw8nFMunz0KAqmX3FcLNC4dxjGkCIn0lqZRUa1AJkfD9zkm27ZUcZGtRpBedlLBKvk9Qm33gcDDhFYji7IxhOIVnyfj8ptcOGZN/87AGR4VTw6+caaosife7hzAF6eztOhqyN/FnMuwQAmAWvfVTHC8CJwMR0sMUNkTOcbDRuSWolezipsheZKWcju7AUGAIAirbZY3e0jKg1Yv+lBuC01mBjn8/9hwhVmEeOFNL9JR6f98D5yzE0KLK1Kgv8qRezeyS1QvXoYNFl0iwnVNK/F9vJPGrdOawXIRm2MXIPZ3coNMgYSJG8Q/tCg/Z6OIGZpDYC/VpSS+x5/V2G2CvRaACupIjMSIvh5D6Im+07sW/drNVNPboNBjGlRXpW3Q+S2kyCFiW1yc8TnhGDM4R/G84f4i/7NzF88NPx+agDkJzoov+yNXaTwzl2mAhw1j1ZNdLfnZ0Sg56/gGqG080ZzoF8ol0DcBrr8LK4SgC8ZjhboUFLg+4PM86DkNSCpJbTa804BvY9a1XCTKkUSMwNUCY6itL7ERk+/v7GPBCLR7qbhQYJb0MrH5ZBNiS1yswBJ/cRy71nBbtKbRwC4GTWITumA4CTF+5GbTAIA2OD534g3zt7kx1F3dcyLF60KOFDaJDsqQ/n/Lv4HDT3A0H6xFVuGdnDBsPpDaYsNChs954YTl6c5NvL/FSRzUN6b83bohjYAyInz4CT5N5L+yyz+Y3PBYdoMfOTB9nxnCAppCql1GZz/xFDdQsMJ1kGQAtFJ0hSKzLJnpSFCknrPvo+E8Opi3dCIallhrPZYocKTsxwsoezMe/TgYTfq9+LRYsdUwRbtTycXDzf14eT7x1OqQUASSmeQvfhPeS7xZTaSZ5FIpp4/2hbeGZUTKgFMh+eywCn7wqGc28f8hOHj8UGdzRrvm97yM5fTBpd6rXc2k7l2ZN+nqLroxy4lNTWDGfL48iMvd4jUXczwEmS2ozVPzjy6xp3PPNwxtCgYxnOPKjyjgwnhdvJbQk4nfeQwmEtDBIUNgYEP7BkwHkgTdeRuixfm6ZzzL8jSszxER0vACeC9l6Lkh1T3kTwKLmtwqwVRgCck3UxYOXWZwxnBGnLp1nlHs4jJBmLoxVTTePMEmhrSGqd3uAlPAMAPHhIL4rzlwPDaZM3SzVkeGkjy9VpoSk0SLjYINkJ3WQ4cw9npyWucZbirOv9ziS13SEPJ7FfVmho4WBbnyX2SOxjOIEZwNNKYvRqzo6KedNzAJiYsV1YeBjJbOoN8EP/PvBvfl/2w3Ac+vbt1Qyn6EJKbZIekk9NYB7HztVRrnZHwGlxJsLi4/ziEj/lP4YHH/yleG18JQ/2MvzOuHBNtiYwpqYPlfBaUqsLSe3Y7olZhRbki2o26m98qLo3AafzeOLTi6hu0Nz0cC4NZjinOeCUC21RZGQ4A+AMMtdwLXfbsN+Pz/siNEjmi7OaXeJeuPz9TUltepa5mb3LGE4vdWQ4Wym10m4DkMqe8+jLzJ7nnF0VGSPgxPyzBwEn7bMhFt2aHYz1uBjCfuZtUUIfztrDmf4u9FnsC7zEcC5JalNfP5Ji0TWv7106AXEhb9cynAw4D3o454Az9uMjNo+/KzKcda9pb2AOtHLwxPRp2GWPmpShkEf7xB7OyHA2WnUlSS17OMO+xvnsSDZKdgN6YRYYThUZTgcVAWICnLp4R0vdw0EFwJmBUmY4hUAsdIRfYA/nfL+iFYUltCzrywK3qgMJ/6uuVVFAthYs6ZR5b0gazvl4eyx5OGXG+HEfTgAQtNaB6iCJ4fTNlNrAcHLWAQNfBpwjdEyoBVLBjRN2+TOxLcqHJKnl51U2GMTTtkehQQXDSft9BMMJUV6zMIeX+xd7/lIqKg8unrECqB0aFD4zYJkECO+O3MOpqNAyV08sjpakNkuXvRxO8HBSGqyL76m7rYs3Z+GdoWaAk56DIzycoTwfEoq1FFRoZRZ54Z2hhmLtFf6xLKy1rDEfxfECcAIALYxNJam9pZajkhZDLQ+n9OHG5UVmktSm6qja5+GkhWgPc/RLdulYwvfXqXUeD0A+qYak1usNXkIApI8fBwZUDpc4F7vSw5m3Uqg9nHsZzgEaFh1MrNaxx28muYwPo4SWEs+xgd89ax5u7uHUfr+Hkxf/jhb0TbkgNaBuM5w54CzvhRDeoGb+z8BwztlUZjjlAuC0eTrvj/w/gS/8+cTwMfP4/Mt43NN1PgCIRE+S2szD6SGiFCqOrAl77OGlqVUHLDbEcJ5fPMB/ar8D57u3gR8mS7eeA06N5eTg7W6HQRg4TnutwE0HE/sYOjM1JbUs11sCnMY6nBPD2S9Ial/OAaddYDjXAE7282U9GQ8xnJqe/3HcoRMEONnXSQzn47OuYDjhkj/PV+ySoZTWEW2QQTsVjk3pCG45WVSRAkHHlNr57yu3xYjyfERJUHb+i2b1mS/Sc0pttm+tljXF9umzlgHnFO7liyFc/10mqW314SxkWd2B0CAsp8l6CsiJHsnY47LFcLp0HawN0rhDi2r2hR0AnKl1VJ5eSYsXb0PhgF/vdesbGtKv6H0oNYQ3gXlcegaynoFAds8Twyliem6L4UyhHQYq2AyA4yW1qseQMZx5DkDoM0znX8iQggmXQL0QZZ9C1RFITSm1Uung9QZw3qmiIOmFWrRowBkYn/q1prYoS5Ja8py6ORudbxPk+UsFw3S/5Nag5ZTaBHC0TAxn7FlMDOcI3S6mTDcEOGl7FeDc+Q6vXKYiqMiTVSPg7BI4+dAYTgVOqb3X0CBkbVEY8B3DcFbJzmgwnCwFl/DFc67ZnxkZzkZbFF15oltgqGI4e63DPXVUSi1Laud+fSEltJI479s9jRcHF+mzVnx3GZu+h/MCeszk7LTuVBWY37tbsS0KhQaJkuFclNTqDUlqy+sNIM5zvhH+91EcLwAn8oVxmpyVt9hKqoyYANREPaGoLpqIWUZ3w4AzS7jb10dI0+Jyg7FdhTpysPygTqecrMMjBpwNhtPrs+iFfPXJk7CtfoMBE6bCw6mTvLDu65ZVlWf7pTv0woQXPbOw5AusX9Qik0N1SuC5P4PfthlOWzGcY6uNAw1eFDoVXv6tBE94B+eXPJxD+88IgHOCmifcytCH08T+lx7ee9jxAOBkhnO8AX7hv6Z/JCDDEie7wyf75839qYckhpMX5nnfsyKOXqq06GVgKztqHWSih/P84gH+mP8OvLf5JPDfhgAd0deAs9vLcI43xIwOgVGvZYkaBreCPXJjW1IbWR267tk17f2IrXE4FwQ4615YCM/FSy4BTu3LfVBHMZwkIcwkaHxMauH6xNCgLT2bqoNgSS3NKY/Ou7ItSt5CQJYLF0OAy4rMM1WPLDRIdHOGEyp5OFsMqbI77ER5PJwEWjKceQqjTyCZA4ayz3Kv1KXBhQTLAVbTDqP1sf/wWPXhnEtqs3u8P4NToS1Kq09hkLftkdR6n1jmPQynoMRr60XycB6U1DJoPAQ45yyEFALGyyipjd8Vi5AVw+lMSAzf9z1SAy4UChffTxFwknrC1B5OltTOPZyR4QRKwHEs+NBLDKdMLBczzHVbFCHL+0N2MTQob4vCi+ZCTgtERqbpVecCJic6x7YoCwwnKAegktQWhSNvIlsuhYjyXx75+3SpD2fOcEbpLDJJreqgpIDxqpkkj/EGozzLPJwB+CaGs8PQ5SxwpryiY9khKZykNx8S4OSFvL8fhlMk1pG3F4sVRwAjV4cGNfaPJbWyUlxEe4APxYwWmON96vZIamM7I7pvWVLLlox9/ePTFzXCH6OHM+zzg00q1qwa5JWMCpk7FgrOeo0RGv1IlrHN41C09aHwsvq+kApKJJDKHk5+Vlv9UIFA5gwYy3VQRqrQxmftzT6K4wXgBElqYWYM506ExU1v0mKwGJJ18i40lUUlqeUbcU/liwHngOleAGdcsFTeLeM8HgkGnHMPp8jkkK+98jIAQOoAOEeb6ekz31ftCYoLmsbkJnVPDKdNnh4CYzNAkskNtAqSWr/g4bTORx+jxrQYkgAkPxoznC2fa/TGNFNqlyW1zHDOenhyH06a1H/wX//T+Bf/2E/EvoNqaANOobvAPnzhvwO2NFFmQJPHb/74ulAb2Z9hk1XZfCFxzCW1qQk6h8NI3QUJorDRwym6c5wPPf7k6393CpqokhcD4DSLDOd4y4CTJLXVgrj3E7bUZsiaKbVY2RMalN+TGzHiemdwQSA57/nJw1iHl9wHYX9EDz0LDTqG4SzBW9it/QxnRyzQtCNJqeogutLD+dJ5X4QGiUpSWyaEhheioXPUAox5mjSDW2dGIFZ8VWTLbAOwdm6LUZTnIwazuCWGMy2avJAkqQ37du2HFYAzbIt9wnYMDCdLtngO4T6c+xhO0Z3Byx69WEqpdXsXv4I8nF7IxQA12mkYH4pQnnonHgyGiymG+/08nuRXOQvBCyDvHbG0JfPizZzhdAcAJ4jpY3/x3n1mwMlFFipmcMG1CJTKGU5WvOTLkWOTKVXw5O5iH05mEDTJ1agPp1AQ1MYkT7IVCwwnvyNk5uGcA04drCKNVw/3OlW6C8d5iOFEsHzUktrC0+lMVKjI2PojfXn+DlzycMqM2RFCwFAyds1wGqi5kgkApuuC4RQCBTu2Q4dezQGnyMIUR3QJnPgV7P9Jg9uYrGeyDm4Pnlpj1JLaFe8IHkIVjFaYTyqGk+X78MWailNpQ09z0VRjcQEleqJbvdGFDAFzeWhQ9gyKNawkpdy3ACc/U598co7XHhzImMgHtZKLhMAdU2o3ncSIDv3EgPNRYDjhU0r2mt3KfbGNPpxiaW5XG2wwFesgEYtdzHC+CA361TOoR2ROeSsYTCTf6ijlcqbRp78rWBhKpsxTat0K0zNL6gYx3fnBAjK/TLVgmYzDYxAb1pDU5oDzrddeoZ2joBljE8PZ6Rh3b6fa77Y8uUnVxZTayHAyA1YDktiQW6FTEld+P+DMJbX7PJzMQnAoS8ufJpyds5Q89oQGSSHo6FoMZ0qp/dl3b/Anf/JteGI49QLg1FJikgPws38q/SMBGZEtbr/x7Ol83xqj9nDmjabLOHYVPQ1RUit1THI+E2NgiKXEg0HjT5//DcDDj4XP1YsoFQo5k/Vh39/7y8WPpy1dU74fq0V7BxMbi3szQdo5+Isve26wTtswoscZdrjaGpwjALehyXB6PHLvAcND3KoHDYbzmJRa6klnRxgG9nSP6QUPJy/KLTGcUvURBPKc8vi8wzZ/WeXhM5X3Y6LkV0uA0Ln5PZ57rWUOkrNFOhfCWpJa7XaYZgwnMQk5w5l7NDPJWC2pvcJ5OO97QBazY06He8ybbZBLzzycoQA483DWgFORpLbl4YRdXJx68j3J6OFsy1XDzoS5xEKF0CCsDw061IczsYWZpJbBh7Op5ySQ3lsVcFAHUmrD7ypIb6FZ7t3+ULHPUVLbk6SWA9UaHk7hbXxflAznkQEvekCHCVtiOOeSWhfDoOaS2mQjCIejKRzGJo9hllJbJNTS55fabHlnYaBCaIre0DkSZfGyGlHOW2wnX6yGVhls38iDXoCa4ZzfR54kofk9brif5sRqrtCHM0hqFxhOkVJqY3gR/xhd5XOdM5yjzz2c+4s8pw5P6dmyAehOGlloEL8/Y4F2oajY3i9VFArz93H6DEtqlz2cHrIZyMP7lDzRjXMrq9AgpYpruEpSC5DfubRPhM2H7/y3f8934B//rd+4altpv3yaL+54X2y0wg46FZM3jwA7wTmSlq+V1FJxTtM8LiXIw3lAydgFhrMgQzIFBtCQWH9ExwvACYQFVi2phcWkwuJmsMw+6NnvAaGKxL6tm9zDuSLWWXfZJHUvoUGVxJDG5FzGcD6e/1rfApyZv4tbKWQezlnvuT0eTtmF2HoNC4hMUisagDOT5nZK4BqbxbYoxwDOKNHgl31TUksptQdDg0oAoeUy4NQiMZzGOfylL15FCaUeLpv72mkRFvV5WBIziTkwe/oLtD+HUmrPsMk8nHmoSMG6NDycIvNwnlFbCQC43Gg8nQTwvf8IDCTc2cvld0qNjq/vX/j3gH/texJbC8Ds+H5seDidhRIeW1IZODsmn0j2PHHicWRHaRujvsAGE57vDC5EAG4twGmcwyP7PnD5Gozo0S1Jalel1LIfOzHtaz2cbkyyfQ7yGaOHsw+tiXxK9kzMVNkWxToPJSwsN+Ru3uMZw6kzSWj2/HJQg20sWLXbYZTlgpmlpnmlu1BA5Asqai3CP7/yVKjY14uTtuuonYSbtpisx2Xt4fTtqrWqAKeTPYaFBGW1x08Wj5PBI0tqGwwnqyVCL0tTBI0sjpWAMxXlsoWoRJDJO1eyqTFJsuXhPPDOoWC8kFK75OFMYUVAOhdctGj1beb7SjYApz1lWaJ6aDiMXATNiirRCxcltWUfzhCUJottOaFDUSH2y1NRFnjWV+eMrCEtSa0khlNKpKJgf7EXUFvomaS29nDy/Zcktblvc7+Hk5Oc87AUS9dWT1eYvIKUIZBomeFsezgBKj6prgzeyxlOKgZM0PG4PiwPJ/eaDIDu7tuPHu5MkmzPnsB5gd3w6vrtQBQAowaVQIDJogWWRWLaHARUK5CH+9ruCQ0KoNeTjUhg6HUxP60FnFboskCSpdQCwINNh01dpNk3qJXcfTGc4T7Ojn94AE6pPcbDyfvRwUIIkUlqD6T66jP0wmKayjZhNjvXnvvFfsTHC8AJBCZGlKFB2lsYBpyO5F41w6kSwxlDg3wCnDFwYM8D0+XMxz0wnDGiu5LSGevxcE9oUM5OdZvQpiL1ndwWyZbMipipXMDv68PJDKeGhVeJ4dSwZVN75NXpUL27xhnEuMBwep96a/ppUb4JEGhB0NQDbblgktQeYDirxZckv4v1VUuVWP0Of52Mw844fPGd92mTbYazkzLJFiNAJgCYyz4/IMB5CBBVk573LqSFopSyiUxSy028tepi4uwZxsiGXw4az3cG+M6/H3+9+ZfhLl4pv1N1KTTo6ksBML/9E/HHlny5ku/HXI5J4HonyG9rpiQzy5/DHDABkWma9CU2GHG1naKkdoMG4LQeD817wOXrsHKYA85jJLUE+nthsvYz4feXGE7NfRxJUit1F9tJ3N4mhhNA4b+NYIL8LvF4yMPpJDOcDdbQ5QUdiZ3XQVLLiz+poPVy2nXndoF9zwd5m/KG9eV3ZxJuCjkxxJ4+p3C2fb04eT7zHTOcO4zWLXo46zkoV5nI/hyePJxLktp9VXXJDGfm4UTLw+mZ4ZQhNGgNi8Pz9yGGkxYn+UJUUWIphwYlhpPORTXfKW9iYvjSECrYHjqYZYaTmWtuTcQp2hSUIyO7lUm/GS9n14oBwamAEwjthcLG0j0eWGkbZdAc/lH4qPLrojIPJ7M1uaS2q/ZPUchJa71YMJz0zCz14ORfEXPAWfhvna0ktaIEnK4sQNXDOk9FqnTv2CipvYmheUoEP+mSh3MnNxBghjO9R4zoMOi5zzXuex4alElqP9S2KPfMcAZwELY3PvgEvmf3r+Dtl771iP1SDQ9n3RZFUHGrlNTmwGexOE6f7/eFcEUPZ2hZNWhZSWpXMpxCpTUbEK+pWvn7syFDCJfLVAp3HRNlGqA7D8+hs/Cegf5KSW200IX3b83qL63zRbTNJNtIXvCn337BcP6qGeQ1KyW1FpZeDBckyVvycHaws9Ag76aM4VyWWnQZw7nKpH1oxJd7xXDawHAatQG6uZynAD78QtQsZ9wWvfs46KSW1Eq/XE0T5OEsWhYoYpZnHk6uRAt0SuDKn0EstEWxzsUqnvJmr4eT2abI3Lb8bfvi2XOGs5KwBoZTxlYjcUhZBCPx/n3h7RAe0W3a4RFaCYwEtvDJ7w7/JxBWJKk+/+J831qDrjn38MxbPxQyP6kiayjciMmrUEGlZ+RM7KL/6HLT4WprYD3w8+bJXGpGi/rROoCkWngnA5wMss7JU5wtiLmFDTNpzk6pyp89T56BFRc/OM20u8RGjHh+u8O5YMA5zliI0To8MO8Bl6/Byj0M55rIe7oGAzKvLC3WuoWCgGbZIYEtofrYfmnc3UJLEVt/sI9TFpLaAPQ4bdVYR4CTpZ4t2XjGZEoRWpyYXQY4dfQJtSS1nd/BzDycQXqJguGsJbV8n4kgCYwMJwHOFQwnz012CgnEm05BiAxwcluYGeBM1092Z4DqFiW1OXtRj+A/9UkCGNM3W21RwjxmIQPDCTeTzc1GZDgPeDgJvOW+IfYUwbnoV6QDpv2ZA841DKeCSy17mp+h8DEGlLYssnBKrSs8nJn0tQoNOinched0miNlBiaD5M9DcaGGpIR5+61iQU4gVeZtUTJJ7XnFcAoOv2uGBk0p9TwynPsBpxUq9UXm78h71noT5+8I9HwO5kuJ/WyXSAWQM5wsqdXmOSZoSBHSTyfoRQ/nTpyld51I1gwje/S6uoZ5mqkzcJAwkKmH4Rq5+Qkj9c3197N9ktSHViXheLUU+BKexDlz1X7NUmrn++epx3JQbOQ5C5QuzAxnqzg+k9S2UmqpWEmAs9eylNSuXI+Gub9k78Lvn3a+uSAU12f3sC42DDj7y7C96OFcf1/w+ehEsFxwgS99YAlwcu5AVlCltnTxr9yi5iM+XgBOBBlbhxKsaLhYTeeUyxmQyjycbioBp7N5pPo+hnMeHX6XER/yWlJrPR7hGlP3sPl7DDhHeZYmN52BFFqsaK2z3n3lImsfwwnZoRMhNCgugES7bYbwJj7InZK4xiYwnI0XurVJUqv8dMDDSeweA+kGezOvPGUjZ7kqxkuRbMNV7KigYCRH6bQMrt/94AMAgD5bAJw5w/k13xf+z0mivLiNIEgclmNzEWGiKlsm7ysWeFLGe0jaMUmESXZ+KaeM4VR4vjO4GcN5PK/CNETu0eXJNgOcjiS1+oL6vuaSOyrgjKQyCAzn3E/pY4AVM5zUa7ULDOftTSpUBElx1Z7GejyY3gEu34BpAU5vghxnzcuzkNSmxffkFXS9AKPR06Lcc+slrWMLhd1ui7NOYUOMyo5ktd6ZWBQAyaKSZPsIhlMEj/QEZjjp35VGRwxnq3VQ73ahcJUNXtjlzExe9MoLHI5erobY9mfge3NPL0726PJ9bMK17LVEr2QRGtQJO1uk5JJa2Z/Bq6EdGsSL8T2SWgFP7WMSwykaLJDwhmT2Ct5OVCg4FBpE98lC/8S0m/O2KNyTEdwWpQoNqlttrAkNEvTcd3sAJ7NcCXCSEkMNcRvFPiPzcGaSNgacB3uVtgbnCnBLogxM8sI9gnD2cPK1bzGcFOoiIsOpMoazvIZe6uIZzIdwIThKSZFsD3sSaoE2w8lFoh06+rMPzCYVGXLwkr8Dm75SYnZyySQH6SlzjQkKUgooITB5PWc4SQ2xW/BwTqIv/ZtAdg8GwBlglEwM8poAq1MGKy+8xf0sdyk0KAMqzDB2R/aaLDycjWJUTKmtk1RpblMisKLNliOCyZA9DGcsvITvrhnOpdTVergFSa08tCZZGlJBi9Qn9z7CnmwEnBdh3ZT14VwdGpR/jkODfH6+2tuRDDh3JeAsugO8CA361TMESf/iRO0spPAxoOIStEhv9OEEAC0sLDEsLKm1dsr8H8sPXt/fs6Q2+nXmDOdjcQ3TP2r+3vkFeQnzpFFmQu0ubk8pnZrVLzKcjeNQ3P5llxYgaqFPYwb6NLVFEd4lsJQNa024VrIPsiZnm731wmZLD2dTUuv2tC4QWdhDE3AGv5aqPZwUKJFLndhP2A/txUenJXaiB4aHwFvfFv6xBpyPPk7HM+z1BIXP0H6bBDjjAi87XiFVvK+l3cXqfJAgWpzLMYLXB0OHd5/vcDOGe6P2NgmdMdjTHHB6YrS6i8Bw5gti9gcbCu4KC/Y5g+7rViSR4XwQ2sBcPwMAPJcPcFZHkyMEgg3uBrh8DU4NqSLMp82PB1tHxMGSWhhM5Af3NjAcS42vO2I4JV0XpfvYTmLcbbHpFTZUOd9OFtdj6PYaQ3CEhBapz6uxAQwx4KxZLf43i+Bb4157sAlwiszD2Wod1PkRpvJwQgjyShmMXs1+N6a60j4L72BM7eHcI6nlFGL2cJKk9tve+6N4Sz/LGM520UstSGpnIIF9iItzACilskqpbbBA3LrCQMI7u5c5Tb/EBcP9i4/EcGaAk/x8sZXCgbYo4T5ZJ6nVsLHQuLTP8dzHcC9qtdGweaSU2tRuxUfgeTrg5IToKDGVOrbs4d6kQtQLWlG+s1RPkkcbz7NSOi7saz+akMseTuGmpHpZyXA6qWcMJzMiBiFQKG9746EWGc62h3PuXXN0/ropMJxKCCiJtoeT1Cqj3MQ6XLz3AEzoMDSClcL5MFFFxMcCYG8rorsM9sbdJ8Mp4SldmQqzkpnO9dv3JKHke0ZUvTZ53xFDg+YeTgCzAnccsgKczbYoxCQ622Y4V54vflbSTjHDedr1ZNWGj+qi+2A4ae7qL8O9eIKHswgFEpIKfNn8u9D6hQvIbLsD+N1QejgXWyt9hMYLwAlmOBPg5PYZRgcQxpK8mayOANkZxijp45RaZ1L8917AmUlqT64IZSMmAtZtUYjhNP1+hrM/e5D9I4OUwHAaL6GUjMmas2bn+xhOWnycYUzAnTycNQjIX6adksnj1ZDVsl+Iw0SihLMxasDZSsUUh5qh86Kh7sMpBP60+yb8OfeZWWiQRAAEMbBHIPaz1JuF0CAp8KP9XwV87u9K7CT3t2PA+fgT9OUrIsc5hZgltZmnrpbU8gQv3RgCL0SQ1GphcCHGuK3v/vQTvH8z4U/95DsAQkP0fAjVh5Rasx9w9hdPwj/kkjtiOBnYeDM2JbWz3pf0krL9A3TCwlwHr+y1fgmdsJh2WY9M7/GIWqKwh7NvMZxr4+5pv3oxxXvQW4MJqmwRkP8KydMVAU6p+9izbxq32HQy9rPbGYdnt1MAnPwS5kUnS2qdC+oMXoA3GMq8B2unBLa+hx9vk6RW6diHs9U6aPA72OqeiwynMxjRALu+9HAK+DjPXkWGc1lS6ytJLcwOF/Yp/qa//E/jt8s/lXzgrl30Kti5bhPbaMymigO+oQheYMNnmLlpMpzk4fSKgl7WtEUpA3iWRlqYpPsqptR6G9qi8Dy2wHCqlQxnLyw6YReDr9I9WIYGxe/l4kV2P9iYUpsYBt6Xg8FKrREltQQ4sxZdLF+MzDXPb9lzUHrkUluUvKm7ipLaOZhSsPN7Ccxy61AYWO3hrBbwdDyceAxnUFoiSg9nruJopdTaCMAy4MIMp0tFRilCb+mZLJ8KQ1uRPJwCiZmeRD+f7ziIjjyczHDycUp8SKFBSOz2fTBl/K6U2fuT74ulomJzCAkFXz4HDQ+nIIaz5eEE9qgBoqT2AMMpQhqsg8CgasC57njC/Tpvi3JU781sMLCLc+o93BccohcYzgA4PQfMHZlSG/6Snr30T0sMJxVJx8zD6SolHal+PuJ48wXgBHKGkxZt9NLyeoCFwMUSw3n+MgDgJVxFbxxLaq1N8d/7Kj39kEtq7w9w1pLakTycdnjc/kXqb4c8NZVekMLsAG+iQV3GxWzVFmWPh5Mr0GdiF49TqCzFtNhOehg7YjgBAI3WKLwPVgemsMdyUm0CnCx7bklq3X5JF5+nRmjQP2V+N/41+9tLuwWxuNb6yHp9+tVLnIkdJq/m9xR/jRL4Qxd/D/Bb/tkUCGSZ4aTjePxJ+vCaBFUK8DC5pJYr5FVokGDAmfmPlA4eTiSG8zd+4xvYdBL//n/78wAakloVZNSjzSS17/1MClghEDqQpLZgOKmAY+i6ejul+yuX1DI7Qtvkl5Sn+9hfvw0AuO0DqI3JuAiyvldBqbmXr8OpAQOmgiHXflrPcAoBS+mnsbjgJlio5ZcvHUtiOLvYTsKOJKnNGM6rLWUh81xBzztLXy17GDk9tSmpTUUVJUNBR47PCsDZamXBY8AOtk6pJc+b8AY7ki+5QlKbxc/TAjkCzujh3COp5We155TaXWzz9FBs0xyykJTNIUjhL6ktylxSu1/Gxf3SIlvJktqGh1N4G33d3tmSdVwasaflOg9nnVLLHs6CMYoeznKbawBn0b/0oIeTwBk/x3xuIrvVkNS6nOFkSe0JC0y+32cMp4oBLfGa0fcpP2XBStl1URpBqp61RZEBNHZKzAEnM0VNhjNrPcOFzv6wpLbl4XQkzw5hRpkUGaX/q2yL0mrVAtTtIFwWAjZ6HcQ8SlCSbHVv07y9E2VKrfcUooMuFsnikJLYdxPnH8tyROfWyc1PGMxwyoZH8qRB94miXowAYoG5KW1d2i9ZBk21vIROqMRwlouK9Jml4swsNKjxnPPzZoOFaejqPpzrrocXuiyQRA/nidczFifuj+GMip/+Ino4nQek8OsltaoEiEC5dlqU1EaGM1foletMT8x5aw75KI0XgBOA0CGlNjGc6SEd0afQoPqhJcD5RFxFti9Kak2K/95Xoemz9Mq6WfkpI/UlrBlOh4fiGm5oS2qjfLbPAWf4N2F3gHOw5O3gFE1XS2r39OHkc3eGMS1AZAfV9HCmxVJIqaV9awBOXmDkDOdicFDFcLbZnwNJklylbrRF4dFMqc38m5/7xGOcYcRWLAPFTskU+JAxzaENDB3HQ5LUHsFwCsuhQT71RcyONwcbyu5CkUGKqAI4E7vUFmXQ+A3f8Dr+258NLGLdEF3oPoVxMcPpLfD+z4Sfcy/SzWVY2GSLLJZrWwL43k1ZgE96ThSlrDIYj+0z+sDUy9t3AQC7IQDOKQec1uNV8UH4y+VrcARCpiKtekr+jxWDgUyS5xtKqVxYGBAY0I7CTnQfk2vNuCMPJwNOh2fbCRouLv5Z9sSL/YkktX4P4JQ+sV9aCVzhHGJ8lhQZWWucVh/PHiOsngNOUTOcC5JaZkN5nh1JSbLGwynoOTfjFo8odftS7hKjvEJSi+4MUD0GYWDr4hRLdxfnABGOgOcoun5ySVLraaHtzF5vaPolltQeCJDgRV22SFWSJbW2DGGJgK+Si6+U1PKQC4UtUTGckZmQpaQ2L0DYwsNJErp7kdRS4cmnd68jliteMwYKfkoL9gbDKX2WZEvH8L/5W78Zf9t3fKI8fqWDn67BJuZqgvjOOMBwehHei+V2DJyQiXlFkuQx684jn7/sSkmtzxQ7OcNpoCBmDGd47rZiiGBLyAR+RnRNRYflkCAXJLXxvHibPNH3PWRqLXIfDCdvQ2XBbYnhPEJSSxJK59NzUKfohpRaN+uZmq+vFgO2VoYGAeGZYS9o0RZlrYdTtgGnOlVSGxVW98dwuibDiaPuC5kpHPncrGE4NRVJ/VhKasv+5ww4V+3KV+x4ATiRFsbsd+CETEiNCR2UoLtggeF8Iq5iGweW1Ho7ZRLT5QdGd9kLfU+40NoRQevMw+nxGM/hlhhOfgnm1dfIim2T7wupv5qrZGRin3yDXrYDxlQpV6HVxlxSmzOcmaS2CTip1QkFMdRpw8VneQLrGMS0GE6D/QwnLbQrSW3uo5DFJBRYXGddlDd988ce4VyM2KLyweVfI0U6jqz1wmgcBpDM88Hr9OEVDCcdc2I48z6c1aSZSWpDYqGgPncWGyRJLQD8zd/yVvxznd4oVdb2ZrwGLl4LP3j7x8N3mZvI8lqootecpUKCJR+1t1lblDxxVAiM6BLDyZ8hwKm3IQ3YbMKzmhv3J+fwqiCG88Eb8GrARoyF70nDHAU4nQyAMxZR7IQJIZynOVQJOLXuYzsJO+2w6VQmqbW42k6QcBFAxUU6M5zWQQuX2sW07vGMddFS4MqfQ+2ukodTdUnmWANW74OFoBEaFMI5DEbBoVzlIiSXcAvvYGn+MB3J+Pel1PKChuYnO23xWASG80JsMRoC3GOau/NRyEG7s0zlULE3fv+c7UUIaIkLZBlkji3AKUkVYkiWuErWtxJwutx/yN/HIRa+YjhZUdJIqT3McKbzphZa+/iq6BGSWWVkZVgi1/JwBobz/iS1IjKcQSYIKeP9xiCc90c5k76r8nCCgoaQ9+oE8IPf/gl8+tXKBsEpu60CpjNJIREZzhM8nFTwDaDNUF/JBNBzwFmm1LYBp4QvAIXLipbJw0mS2pmHkxnOs3j75aFBTYYTgblOoUHJ8wlnwv16Hyn99RAc8rNCXbByewCoIEB/5tCgIxhO7gXrcg9nHRpE13XmM8wLBUuy19gjfp+klt8dU0q7zba9NjTIc0oz32usCjh1PcvzFc/N93Bf+Mhw3sHDWezHnOFUC8erBlovmUxSmxV9w3bEokriozReAE6khXHt4RSqS0mhwNzDeRZYk5dwFZm2QlLr29X2fIiMKbuPlFoGrTWzYcwOl2ILv1lgOFtyH36Ju130kACIDKevPJzC7jleOrZBmFg1l2ofw9mQ1DY9nCR/ZsApzGIvTpbUir0ptYcktYcZzgJw0rFab6Ok9sFG49WNLe+tanRKJuCTMZyjdaGdg+iBSwKcaxjOnK0GV9gYcJZmeF6IKD/FvqIsOx/8rqjQ//qvexUPN+EYa6mZ1FlK7XQDvPkt4Qfk45TmFrfU+sUKXSyI/cTXlfsuZpLa7DmUFHqTACcVIDbBq9zvAuC0Z6EpN/f+BBLD6SCB85ejpDYHnMpPyf+xYng1oM99xMRwNqPrAUCEsKmBAKfqugg4tZ+wKSS1Ds9uQy9bucBwGmIj+B4/5FPWUuIZziHHq8giSpIUhl+vfp8KazXgDDLZkFI78X2dLVRVwe6JwsPJbLTdLQNObrEiaH5y0zb2Fb7ALj7zN+zR3ZNSC73JijhVb9YDDGdIjizbShjRtRlOMEhQgDfrJLXREnEoIp8TVtN+ciNyuMDo1G1RZh5O2ChJXxpFuu9CL9rEcNLi2U5Fo/UoNcsVDNG7lhKF70dSywynywpqKno4nVAAAUCZFxeLlFpNSbFzhrM1eCHaep+E72BJ7fqUWoVyW7wdC/Z3loqBXFJbptS2PZw12y5Vn4X+qNDYXggYrwMYyueRkQHnEH1+uYdzt8BwGk4zpd6kCXAyw/khpNSC+3BWLOGpIwLOxEh+zasX+E3f9Do+98nHR2ynlNSKxtwQi3i1hzMLaFpcq/D6iZnyhdAgILxbU3uV3F6zEnCShzned3dkOHm+iL7Qe7huHIqF/iKsRZ2N7YHWS2pzFcS8WL+0HUXvc595OOEdbMVaC/gXHs5fDSMujCPg5NADnfr3APMbqtvAdRfEcHJKLb347DpJbQ7O9oULrR1LHk5/G5gcf/ZS+xeZtWpIaqXdwXuXFqkUdBT7WvJ3Yx/gTIuVuFgmENP0cDIDo3JJbaMXJ7c6oYVo3gNxNiLgXJbUHgwvWEqprRqwx2OJHsMEQrSS+OqzG2y7hWsBktTycfBCxYSFdY8JTnUJcK5iOANw05YnvUxSW/s2suvHqbtCdehh0PttwXAOWuH7v/lNAHNJrdRDYpzHkASLhx8D3vlJAICabiLLa4UuFu3McHJSNNyUqv456yLIZ8RAmkHTEADnZgyAExevhO1mDKexDg9xg0kHX4cnwJlL0jo/wR0rqRVTlHULVy6+W8NAx9Ri3fUxubYXU9EWJXg4JyjhEmPHHk6aa1imyi0pFln8+HwJPPPnUNOzrNCmEwioASv5UJw+K/7ZUxsJ6W0EnAU76lMKI4e4RIUEFcGmbeP5zvYZyAHnDo9EAJznYhufrZvbNsOpC4bzPCau+gXAubwIEdHDGSVpUpd96GhICsQxkMCRKbXiIMOZAsh4KFqIsuQyLtQ4Lba6FzoY+APFFJl5X2W38Nmq6BHCxnL52ZwBjN7CrA8nA6CTmCj2QrsRzvniHcI97hSxvtEygAxwFn04O4RQF7vqHR7n+AU1gREV4DzAcHqpoevQIG9hhYqSWtlQDPA46OFstEUJfZ/DOZwQ+vNK7tELxFY34QMkqUXl4aT92XmNodGTMoBlTqnNWnBECfiHw3ByseFelrs5w0l/vhg0/o3f9e1489HZvt8shiffb0xrbng4U0rtPME2FlPWSmob81kslNjgZVZSrJKIzo8l5FTEe43bopwaGsTPpwtt2Q4m8K8ZOeDkPpweczC/Yr+ArMhWMJzt4+0GVmmlZ2gmqUW4T5u9fD9C48MoKX3FDUlyQWY24qJNdjFOeYJG17jx7dnLeGl7BZjgdxuRyU1XSGrzn32Yklq5/SD8YfO4/YsRcM4ZTmXHUoYXQ2wqhnNvH87cC5QAZ1tSm6rznRIpVGT3bLZZZyuGMwt/qgd7UcReSa3dX2FfSKktJbXZ9hQvRhIQ7pXAV3fvQ3z8s8tfo0SawPm77I4YThNM8BFwLktz4+hS8QAIx+kxX+AJqQt2xUCFYp7q0IsJnZ9mFfrf+9d8Na5Hi0+8VC6kVNcBkeG8DqD3lc8A7wRJrbK32JH8MoRhZAwnS6X7FBokPbUYEeW5Hr2eSWrFJrBm5+aD8LlLYjizYJrROgwYo5zMqw0GjLiuJbVrU2qB4A3EFJJ5aX/2ph4DsNDYUGqx0j16rbDzGj0MznoVF2874/Bsa6DgoOjfav9cDMLqlhlOmSXkaSlwhTPo6TnGaYQCQlp23G75jNjxFgqAn3k4SWrqDYy8ACyADGAUfeaEALwPSd4Aus0FJq9g9gDOyL5SGyFndtHDee63GcPZ9turPDSo26R04wVJ7SLDKXLASWBfdNCNlFrpLYRUcC4BzoOLGz7vh1JqG0BIsgfLO6gMcEUPZyXT1DhOUquXPJxc7c9Cg0y2XcHnvkippefD28S08P9PktRSWw8Y3EyWfMq8KAxAh0F4UnBkktqqDycHDYkVDCf2MpwWjsH3ypRaL3SQ89bbEQrW07H4nOEUBcNp1rRFESXjp5XEhB5n2ML4IKnVLKkFQrGW1whZSm30cIrk4dz6Dn2j77DjOd4ZWPY2A4Hh9CuejROGpz7Fs+CdU0cGOO8k0RUCUviyLcpiSu1c9pnu7f2S2r2hQTEYboJH8OwWktqVQM9TWyBTMZynEijRw0mhXvdyV0TAeRmkrXaKklqz1sOZH0+8l3IJ8kIAZMe5LjngnKfUvpDU/ioZUnehfQM3D+fFa8ZwLi0a/dkTPMEVYEbs0MeFjXMp4W6vJCCXB96HpHaB4RQEOMXZ4/Yv6hbgDItKRZLa1BtTYvQqpb7yd+yTEDekw1IvSWrTZN4ries9bVEi6O2Th3NRUksshOCApKbc8AALscBwLkpqs7RPvr86KSCe/mJqa9L6GikjaImSWbPDZBx6MQWJyOVrzX1pb5A9nBwa5BYZTpm9+C3JQYXu8YDTmruykvu1rz3Av/J3futskSFVH1JqJxsWKT0Dzp8EvIe2t9hJaopcNTvnlFpmtGADw1knxgZJbRdDg1g2KM4Ca/aAAKe/CIDTZz5BYz0GMUV5qNcDemExTem+1t6kwIEVw+tNkZQsfJZSuTCM0DgT4T7WfWiaPiIwypuK4Xy2nUKLCp4rZh5OAmZRNr7QFoXOo5YSV/489MW8/YB+NwOclQogpvzOihwhDVL5BND5u53zRSom96BjhvNsGHCLAWa7x8PJ7FlPxaJpFz2cZ0iAc7tdYjjLlNrYU3KptdMi4OTjTJJEKzqoBsPJclFDrSyOCQ06xHBG7VW1KGyGBnH4S/VO0Gsktdl5U92CdD8ynFmRJXtOU2/onIWjX/UZwxm9nKdIalMP3JtdYNG4cOilLHy3XJRVuaS2SKntYopoLL7tYzgbHtX4s+xZi/P4gZRaL0O2QZ6WzQtUZjgBn9oMCVXcLznInKUwI12nHER3PI8iSGqlDHOr4XVPDqaJ4cwltZJb8gDYeo2hBTiFDMGCZDNI27ar5N2nDEHXXtxXSm0mqb0T8yZLhrPl7/ZFSm15//G5Xu4ZTgX7fX04C4aTQoPyAMG1kljqNR4L/dy79o6hQcpN2GtvOmbo7NmTGvAW3h0pqW0xnHnx+0Cv7eJd4/0McAr4w06Kr/DxAnACgOzCQtOUKbVCdbEH31JrBH/+Ml4SV4DdYYLGpm9IavdNpPctqdVtKZzcBkmtPF+S1C57OKXbAd7FF3inJCboGTuwtxqcB71kHs4uSweOP8/kNeeDxg2G8HLdExpUAM4FSW1iOElSu5DguRcgrGA4C0ktX1ObQMi5+SB44R4tA85eixT4wJ46anY/YAomeD0ExlovLATzwaFBeUptQ04mlAIypt1AQgoBqbrUj7ZbJx1iJttPtwEQdhfAK78mFA6ufgmdvcVI7TWc0IXkL15X9nBaQyEslWyXQoMQvVthG4raojz0T0OVnqTkLmM4jXPYYEw9Jek85g2ae0xHAU5QSi3fg4Hh3P9cW6Fwzn1Z9YBeS4zQ6BEktYMgMDVZPLs16IVPrFXVkoJlsVKXoC8fIrvHOaUWANzzID9We0KDLPlQ5gynjJJanjP5WoS+fxkjQy9XBsdnmx43GOD2eDgj4NQDRq8AmxjOM38b+3DejnSPVs8wS5ANFKB08nHbSlJ7kNEit5pIHk4nu7IPHQ0JB6F0TKlVfr6onG+eZYaHGE6W1FYL0RiQ4wpPnBNqJqnV/rCkNg9bWiyI8j7TPknX9nD6DPBGb6FLHs7IdJ6yLNEMOCdcj5b8mlmBg8JX8j6cipJf8+8OO9whtDqxqxjO2J+vwXCqTL6+muGUlUQRiBJhJxSEsxXDGY6PR+7bbPXhjNLmPZJayR7OnOHkERnOIfJrQiS27XaB4eSWLt5ZTL6W1H54oUEAAcR7WO6KuL0UGnTahriVTvhrU1JLDGfNRgPI7u0lhpMltcxwzvc1SqpJUiur0KC1KbVedlDCpnuNGc4TGeVC8n4fRQIgFntsd54KXM6gbg+0f7/mfTjLkKX2e15GhVrGcFYM+Yu2KL+aBr1IDU2qNmM4LfWnWgKc4vzlwHDaHUZ02Azco9KslOPcL+CMN71Li1QAULsPaH8XAOfwIDw8FIQEIDGcdiyYGgacNTsg9zKc2cKFFsPco7KWwOYv08teAxCY1EXTwxkj+Alw9mI5pTayXwQ4WxVp6e3+BU9kOMvF16HQIGcnjBQadLH9pfDDRx9f/hopo0Tl8x/chkW82ZKH08AzSHr0iXDtDg0CiSompWUetAzECamLidNkDGfa1v4FU9wWM68jFQr6c+DVrw9//vyfQ+duMWWAUxWSWmIsSULJHs46MVZJYISKk7l0JniQyCf1kn+KW2ygaDu5cX+yHhtM6VzStY2gyvsgOzwCcAo90D2YUjgPyRYtuiip7boevQ7PVweDb3n2x/Hw//AZPMQ1dsbhajuhk5nvpOqXyZJauYfFz4NMOKUWANxNAJyB4VTN3zdbAuxd7eEML0wFA8M9/WgBbiPDyc9FAEUsqT3fDLjxQ8E+zwbNLUprSiVOHs6NDx5O5zx2MaW2nHPZw7kDh341qs758S4yByEcSSNJQZ3soP0U5XE8pLeQUsF4lYHAdQznQcDJEspZKwVJktryuyxKBQG8Rydse67ORpHuuwA4Y3AVh4VUrYRSkF36fpMnWlbM5mltUcL39cLgemeK1j/RwxkltXTv+6WU2g5eamI452nA8+/mBexCcYfBt17LcAbFVc5OBkmthkPoDxok6uXx8cjfp01JbexVm45ZK4ldZDiDh1NRIBuAysMZ5oBbbCKOyVNqb13bwxlazRh46vtYhwbhwwgNygHiPUpqu8zDecrga5YktQ61pJZllgBmAT4p8G9pniKFGKZ0nutRMZyqltSuPV9SocssafAOzouj2sSUm6OEXW9OKz61tknrl0klwBnuO7eayc0tb6JRHFvqw8lzUx6yKetwSmLiXwDOXw2DQw04NZFAjFRdbBi7JKkV5y/jiXgGYUfsfGI4nctSaveGBqWfFT6jE0cuqf25d6/x2X/yP8OPfuEp5BgYTrUEOM9eAn7PHwG+5e9I/0aAQbsdRO77UgJb9Kn3IX+33+cXyIJeoqS2L9PN4nZS9ed8CMczqvMEXLIRWVYCXfvaovACWPFiueXhPLQojICzYjhzaUWulGDA6UysAF7crgCcSsQJ/A/9mZ/HlVFwZhdTamPftB/4PwO/8Z9a3l8eqoODgnI7eB/6CMaFXQ6WpSoqmxwa1Pc54FwZjsDXme49dOfAJ74r9A/90/8qereFUW1JLQNOZiphJyjXkNQSwykySa2Fgiaj/ku4wq3YQLJxP+v1aKzHgDGxddwqgxhO55H8smuHHorgKrlCUmuFQi/CXKG7Hr2SGL1GLwy+7umfgthd4TPiF7CbLJ5tDTqRZEBLHk5OkkaDeatDua5Isu5v5gxnvYiOHtjZPSCTh1OU/lFuw5AWyMFzxvPs+WaDW+wHnOzNVUpjhIawYwKc7gajcXg+EosINCS15IMlFkfw+ZkxnLTAWwBinvtwZn5MLzt0FUAIZ8TBS02so1nH4tDC/ZCkNjKcVfqxo9CgOqAoPF8ZS8XX5mBKbQ44F56DysMp3QSbbbeVK2CdhxB0XfnnzDycsizJJLXXO1Pc4xAh2ZXPf2JQsuLijOGUoajgXAh92jOWel8DVNw5geHscsYILKlVEbTJzBKBCnAeDA1ycxDTSREBp4EKDKcUMJ6PLWc4rwE1wJL6BQivkAQ4VZvhpJRa7wzC00CWDjeRvPvDYzj1HQFiHNm78U4SXZbUEsCQDcmvFxI6SmJrhvOAGiBri7KYSRGLiqHwopUoCivHSGrrlFoHAbUgMT28vSQHvi9JLRfMd+IszTN2OorhLABlTKldAzjnqe3I11/htyHFiz6cvzqGKlNXXdYWxar9klpx8TIuxA7d9Bw7dDgbkqQ2hejseXDVHIjdZUgp4byAcAZf+GAL4zx+6svPoSlwR58/Wf7lT/26svoqBCbRQ/uxeIH3SuLW9xDTbfHraz2citIOJYUG1QAxr952SqLXElt53pTUcq8mQcBkH+BkhlNyTPVCyMMpktqc4VQF+KRrmnk4zyLgXJbUdkrGtNRn2wk7dDC7W/JwmnQ+X/064PEnl/c3G0YNGDAG+aHPJUZ5dV8V96v1ClIKqPx4VzKcXGToxnDvob8I4R6/7n8I/PyfxsfcFyLgDEmfGeAkMKIiw2kgMQdvUgiMXkfJl/QGRmjoTdhHJTy24gyat5Pds6N12IgJnjycIjKcAXBa58NL71iGM/dwumlx7uCRM6Cq60hS26HHhLee/RAA4Ov0F0No0O1EzBQBzkVJ7Z7QIJ9aEOQMJ26J4VQqgalKkscpv6IGnJJ7xtkkUY6AE2XwBftVCBxfnA2hnVRWDKiHiJLajgoMY5TU9v4WI50btZCU3VEPSe4RKqs2GnEcmrNztozPvexp3slWCz6BUgcVQ4PWtBqoQ2DaH2p7Cx0kfbctjsEJhaI5Oy9+DhRTinTfJXBap9RW/T1VgwG0zoc502XA/S4ptZmk9ma0RdGSU5GTpDYFqjRTalUXnw8OLtk3ZBYMN/sZMZNhu+tSaiG7sq8hwjn1QmbXMRUUXCWpjXOPWPBwRkltek9pJbHz4VqP0JAiWEOiNNpm78op+PFD8DSHBiUP563vFjycASw7a2GhIph11h3FNB01aP/0XSWwvLnKd3fydmJIDG93Dny8kKGnMjCbj1LLn/3sZS+Ww41SocTA+UZo0GqGs4OGK1QLFhLdiYyyzMHyPQVJDbQeeG/qCoZzVZAbjcLDyceWdydYCv3ktVqVUovqXpIZ4/1RHS8AJxAXxhwWFBdtqosNY5cWjeoytFs4234Jo9c4HzSMl0GuuSo0KJfU3v3hkpJ6NDmLHTVDf/f5iG78ANd+QDccwdYAsHKIgDO2RVECWwyQtgScct/xFv3cUkW7lVJb96u7HDRu5VlTUht7a/YJcLJ0tR4xwVQz4Lw/Sa06IKn1Nu3XcP2F4GdcalGDkM7LC9jnW4PRa5hxGz2cq3pvVsOqDc4wYjvZsOAXHDqRvWSyUA0AKdI/P97VDCeBGgacDFS/7XcD5y+jg4GhMCO/IKlVm4zhbDSql9QWhSdzToXlKHIgVDX576JgOIOHMzKc7O2dEuDsYVLT6BUjAM4phti09rkeeZ9PoXp0KgDOT4ov4+H28wCAz6hfim1RdObhjL0LPQf00KK/46pq+x4v2qKgBJxa5wznPKUWAGS1aA4943xIR5UaFmImqc0ZGQkfGc7Lsw1u/VBcm9mg49NKY/Qlw6m9gTM7XG0NLSyxyHAy4ASdH7Hg4Vz2L1FoEFxSxhDDWcxjWT9PK1RkONcsUj3kDOjPPhNXqpWkVgSGs+x7Gt5fxfNFz8shhlPnrVAWCqIyyoDDPtXSd57v89Ai63yYJ51Ji+mqH+dRgyW1mHA9hkTaVh/OvC1KYFDSPVlsi5My1wSX8DlsWDRKDyfPM/sltYH9Kj2ckpLbQ39QW6aaUkI0DwaZG62axdeUcJyufZdJao0PNoowt7YYzhugu4DzpYOQ/zb6DkO3BDgtvAsyT5Z6WjvR/fphSGrpWgu7GljsHYV86fTQIE7PdUVoUL09meazVssU7PFwirLY1PwIP3dZW5S8ILa2D2cIDUpFVu9Cy4/F3tMHhiApbifuj+F85XFYR/zlZ0jvTjfRPL6eyY372GiLsrh+lyrMM5kPOhA4GVsuw/3wUW+L8gJwAsmDQS9hBjFS69gyYWnRKM5fBgBc7N7GDhqXg4aFgneGQJrcPzFlN3HhlzlxBGmLBHxIB/1e+Rfx/vNbdNMzfIBL6COrTkb26HzwcPIkp6XELXooUy4Q5cJiD0Apx+IFttJQwmKqAKKo/EcXg8KNaDOcEWgQg9WvYDjji7/lucGhlNrKA8aHVMhSG4DTp/0arj8f5LR77gstJawLselXO4Mdethpi4naoqwKCqqGUxtsxIjbiRkAlpxlLxmlCmlIlOPk13Qtw0nXvJsyDyf//7v+wbB96rPppIbKGRi6rl2/weQVhJugFz2cSVIbGM4O3SYt6nbyDF3XhQp+xnAa50MAE/eb1RXg9D4kAh/BcMouAM7o4fQH+rqimlukDpJaKHxW/Gz4N32GrxWfx3YKbVF0Bna4Cu05YduWRZU6rRooAafKGE55+374N92le6L6fTe1GU5mkTQMIMIciAiCy76VnjycJcO5gdwHOFlSSwynpNAgvjba3BLD2WYEOiVhvEwMJ5+fup1JBhRbI7VFyRiJVvhZ5t8PgT0WqzycoOCflQxnvShkSW0NOJ3QSXEDwHIS84F7uwCcC5+tWXblq2em4Qc2keFMgNPHIsoJC1WajzvY5OEUvD32F4d7kBeGOg/uqPpwsryzSLJdGLGfYetZg02gfm0fTlL+FAwnBekxaMuLsnF+oSIFh80NndybUpsXVTolsCWGcxIagiS1i304ieHMMQWfpx069A3/nkMAy96GlFoXAachj+WHwHDm65378HAW+3h3SS179lqhQU4kwDl/zg8UZ4p3+BLDyR7aUHhRVWjQ2j6ago6FLUCeEpX1iYBTxuKR2b8WO2I8eRgA50+879O5sQZS+COAtZr/uUipXVLFBKWAyJ8hX/adFUIUjPdHdbwAnEDGcIZFTVy0qS4GiizK4qih/IV5DyM6nPchldDb1OB4/3ffN+AkhtM7bN75Yfx7/e/H1/78f4RueoZn/gLdkbp6J4MnDS6l1AZJ7RBbbAAhYCUChgMezuTZ6Sg0aDmlFgAueo1rf9Zsi8KhQWsktVGyGVtGLPRN21dpffLVwIM397ZFKdhONoxnKbXd8y/s9W8CiNdpsj4wnNCwI4cGTTFl85jhqM/kzRhi9SMAKJLpdErWBZKE9RSGk655z4Azr+x/5+/Fu/4hrjYfo33QUMgZTgacQ2or0WALhRDk6aMiETGcSnchzRTAKM/QqVAkkSYBzokYTlQMpydQam2Q1Po1bWf4kGNoUPJwOrH/uS7aAaiOGq53kMLDqHPg1/xGfBU+j50JDKcSmQwoejgJ3Bn2Ke8JDcqeLy1lZDjlljycugN7CWumzZOHU/TVPRABZ2hvwEUvIAD3AqDFCPiwrw/ON7jBAFUpJorNM/OoOuzQYXA3OBc7TBdvhuOwN7iiHqXhYCpJrZSwUJjIwxmDyxb6cC55OMHJkRno97KfF7qK8KFwLtRK+RYD8n3DLQBOHyW1ZeXeCVU8X5aLqweC6gpJ7dJzUPmIlZ/Ke77hB7bOh3kya4uSUmrvwHCKCde7EpBxIqgSNcNp2304pYqhINLtCV2JH9+fUhvfZS99VSjWPXhz/7HQe9E0QoMCM0YKFaTnCUAsQli6DzdaLXg4+T2djktLGQEnK5nKlNrs2MYboDsP3uxswR0ZTmgM3fwa8r57Z4s+nM6URbT7HMXzcZc2JryJjFG8Wx9ORSExvF2P2XI8A5w1WD6G4VwCpfwcCBf6cCohiu+Ra49P8f1KRU93Nw+nLBQI9wNR1JOvwQ3O8Bfe7+N9FtUtawsdBUA8wsOJEMRVAs5K7ULvRPcRR5wvACeQPJwsM8oltRwksrRQIIZTwmP0GheDgoGEdxYiA2mLQ4j4maVY5WOGEIiSWkkhIN/75T+Is/E9PMNF9FysHZYa2cOZQoZ3ix7KJsBpnV9c7AEoAQv/mfs3maqFS+aPAoCLQeM5ztoMp6N0UgacYt7XM34tgZFcw1+POmxjNr71dwH/yI/MXgD5i7fwcGaLEV6Q6uefPwg4OeHNOIfnO4MdOrhpix0BTiw0Yd83nD7DGUbcjpxyOF9sSaUK70YMy8oXm0dKanvDHs5U2febx/irp38FP/LWD4Z9k10h+YMd4bzA0PeYoCDsFJIbK8CpYmgQ3QdZr84dOJnuLBRJMEBkRRJjPTZijECTg3Yc9QC13odF6ZEezjw0aI2ktlyck6yN/u3ZK58DXvtGvOm/jNubG2wnV7ABvGiwDDi5AMNA4QDDyQFgTmgo6tUbPXc0jxT7Sv5WVbM0FeC0UJFRc84XHqUUGkQptdSHU5tlwBmLRUJiEh0euzC32cu3AAAbf4v3b0ZoseDh1KEQN0lmOMP/Z5LaRoJnPsLc4EtGRgVJbaHUoO14qeGkiqzjGpbFQySP5tJnGiwVQPL4BYYzf75iTsGBe7srAOfCfcwpszGl1pZSXbruovZwKhnOU5W4fNJCXgh4NWCAwc1oil7OLKnlIgEXE4oFrczmOSHi35WfDr/DYwjJUiYAnYuv+fXAP/bzwL4cBdpeBwtrS8DpyQ8sfdkWJW8vAqSgoE2Xks7zEVsdZfdHznAaktYGhrMhqZ1ugP6CGM4cgIU/79BjaDGc7D91ppDUOjtBCr/4zN1pVIv6Ow95T9ujPq/MQLfk9h4ik9SW58Znxbul/WS5+CJoy0KDWFJbF17WDCE1lEh9OJ29G8PJBe8OZpnBPXZ87d+A/9U3/GH8uS/5tP5kddxqSW3Dw1lIapff80Z0kNkzpNwIK7I1Fc1RH3FF7QvACSCxb7ZKqe262NphcdFIgBNAxnAGRoabNR8cmafxrkNxPLm3EJTq+or5Ij72/C/iSlwevb3IcGaac/Zw6oyRsP4IwBlf7uFzxqQH0TlOUE3bOO8VnrnNQmgQXas1oUGeAlz2SaD8AdmbEM2Fl86qeTmmz/twjpSKqm7eAR4vBwYBQQIIAJPxeL4z1Apii8l69MIkSeAxo9tggyCpFXmFbebhzL1fd5DU0nM1GGKmM4ZzZxxuXYfLM2KAZZcCXwDAjrFSHprWm7CQrT2cEsHT58jzmQG8BDjP0esQdFUznAMmCPKRskw0MpzOh0TgIxjO6OGMDKeFO/BCKwCtKgHn8ze+E3j1M5Dw6J/9DB1jzgqV7BKzF0qFwlerqKKq0CBAYKcuoal1Eod6OaFmgJXPTe3hhJBZz7cuzHsuZziz54oCM3iBrrsek9xAu2XAmfc0ntDhJRf21T4IgPMCW7x7PS7OQVrKEnDGlNpaUstAblkeleSZNI+onjyc2bliplQoOOiYHLtmEefJJ7r/Q8ttURK4zQCnLAGn4bCkAwynWiOp5X2ga6RrSW1jvjXOQ4GbEFYptScu5IXqMQiD5zvuw1neb3zNYluUXFIb57lUDAXCwvBQmxbBUrpGkUDBlN7ENcGAKrRFyVNqFe2rlwrKW/L8tRnOBDgXGE6b7k0eOgecmdzeeH5/VSm1xHDmBBuvdcK83QCcZJvwNhR+I+CkAt+yquAOowCcdwcv+Tlb26eyvZ0goUxtUeaSWgi1LKldEbB1KFiI1yZiSVK79vhUaOEVJbXEcB5r30rfS4Xqe2Q4IQR+zVtP8M7zHa5GbllG9/Ta+eYAw7mvDYwVOn0fWraDF304f/WM6OGc6P8cwd+l3nxLleDN41hJ2qHD5RAmUvZwrukpFhtq30OFL0pqnY0A7V0RwmmenQI4KdkULr04OxkW7znD6RygBEmUWhNN4eFMklog9T0FCLiKstp3OWhcuSFIaqsHkh9ibp/RIwC71oiAZS/Dedhz1xoFw1n4OdmgbjAZhzfFu+EHexJqgUxS60LvxZ3vADNGSW1cMB8xhCYP51j6yfj/1gtIJSGlhPVcHb2DpJau+cZWHk4Az27DdXu4YcCpoSuGc4TGoGVISrQmMJzVcyijpHbOcG7Jr2f0eajgV0FXkwsFAG6Rwb0rObDIWodBHCepBafUmhSg4ldKah0Ss8Je1d2b3wm88hkAwKPnfznsZwYmWMbD8tTYFkX1VPhakNTyopue1VFfQI8fhH8jVqvFcGK6DT3W6vsvZzqY4WQPp0cAF0UbBx9ZE6U1jDpD77YR8NUjT8CeRIeXEFrtuIdBKXAudnj3+W4xNKhXBDjpnuBevHIxNGhpDggLA521pgEDzoLhTF5SL0M651pJbXhnHGA4F1pueREktapqA+GELgo6fqWHs1vVh5PvQWI4YcoiCkvYCobTYZB8jkrQd7JUUfe4UBY3o6GWJxngFBQaJGV8ZrTIJLVVETQxnIcXvfsltbaUzK8ZqoMSPjGRQOhbK3QIDQorjLjvsZDDBZ7o4VQHPJxZSq2UuCVwyXOPkkgMp60ZzrmHk/dn59sezsA0J6tRDTiPPk9rRv4c/0priyI8LF+LpZRaBpy1pPZQSm32s+XQIFYeJMCZA9vF1NV6O0pDwcVUfe9sAJynSmrpeztxjwwngG948yEA4AvP6F5mietqhjO3HpWWFiAjFxrDQEO6tM7VfoLNwwjF4T6cV9sJP/vO9XLbv6+A8QJwAvGl6yqGU+guJVcuMZxK4woB7OQeTriQUntQjgOkG/4eAafwDnIKzNK/gd8BAHh+KuAUUxF+IqXAVgzQLpPUUjP0RbCWv0yqKrLLXmYszS1DgzQ+sJvwQjdb4Cf+M+BH/2MASEBjc7gPp3RTuI6NEIv4mVpbv3LkILMlqfU2VKw/Jt4JPzgkqaXJzViPq21gOGFSaBAvmI8aXZDU3ow2MCiiXGxZSCgZjiUuBurKP3BEaFA49jPLDGcGOLcEODOGM28FIOyICTq0h4GCdGOZ+Egj9eFMbVGYlR0j4LyAkkEGnss2jTEYhIkAWpEv0ZPs1tp1i/Ji6CH00GMvpTcHF1L8c5PNFVb2mLyCfevXAi9/LRwEXt39XNxmXMRzYEsMDUoMJwfI1CNniln2tFOX0TfI/YCdkPAVa+OnG+zQoetqoJP9XXUBNGWSWpkXkUhSy4W9TvfBqwoAC7LaAnCiC55QAHgYPMAX2OKd5yPOeDeqBZpW4Z42kgOiFjycK9qiSMH+SZI1q67w7YbtJGmup/6DSvhVCygPUbYwaX+I9qfdh7MGt3UKdCzyHWDcurz/7hLg5HuQ7pXOV4CT96NIqQU6WTKcXAQ5eZGpBpwpi+udLSW1MpPUChVaP6FquxDDg8rir1qRUiv3FDDVCQVMZvpy5Y+iIpEXSVKbQrjoHqDzH8PptIysUz5isSK7xzsloiKEbRQxARzAUkpt6eEM+7PDckqt8hawQVLrIuDcFsd9n6P0cN59uXtv2+N0cVbCNAGnyCwCC5LaPffmoWChOH95A4/QUzUHtmvtV4I9xyyp9S5JdE8YXBDq77EtCgB83RthjfgLT0lKy5LaUxjORh9OvQegW9kVbd+0r5RTkeFc/vo/+ZPv4Pv+hf8SP/mleZbJV8p4ATiBTNPNlQ+SeukuNozdF9n9TIbKSfJwsqTWHWz6DmAmKbrLEBIxsENSyM6/e/vX4Icefh/+rPrc0dvz5EkTruznNIoBnZt7OBfPU4vhrPqf5tvJJ9+LXuE9S7+/ew785/8k8Cf+xXC8/CKk/qEdDHbTcmiQkzotRhdSBVdds2rkfoWmpNaHPn1vRYbzkIczbORmNNgZhx0lsY4myEDVCQyn7M8wxLYoyQNU9HMTgmTZBHhRXquwYFsJwGjxdu6Y4UyS2qe34Rl7uOHFpi6KBcJOGNGFdFGS1GrM2UJOUhRUPczB1EgeCaeDd3lXBdN4WujI6OEkEE//7kaqvB/JcAIJtEqsYDiY6Uf63H/TfTv+XfubsDl/AHRneFe/jq/CF/Bt4iegzTXw0lfT75b+Oe4FKFUpay2+DqlFgJQCUgBblYpRzGr5hqRWmC1u0c97rOUv7YrhtLWHEzI0Oo+S2g6eZM2Y2oBTZgDO5PcAPUfn2OKd5zs84EtVeziVxP/L/tX4sYvvApCHKlWS2gMMp0cIm+F9CQfQCA3KGEgvZAR7a2R4zFLu/QyxCbLJcDKbl86Bk10BYlnNc+hZ7ldIauN1ZY/6jOGcF/iscxhUCTgT4DhxWaI6nEsTUmozSa3n0CBSBuShJHOGsy/2Ra3owxlZ0fpZc47SR49nOIEsSRiIQV/hWEJoUH584Q/peZMisPqmoRjwDQ+nztuiRIYzDw3KGU5KqQUWQoM69I3Ftyd21jsLAxW37cyR4S1HjBJA3TPgvGNKLRCUKT727K0AWiapnYPRFZLaA5/hOU4Sw6lVKaldKxkWShPgLNuinJ5Sm3s47w+ivHI54JXLAb/wAQNOlnLfwcO5MjTIVh5O7afZHHlIUvvFp2FN8cajE8iGXyHjBeAEEtNmWFJLrJnqYnuBff3KngkCnMRwOp8ktXt7OsbvLxm/uwwVGU4LNT3HtR8wosO/9Ph/iT+nv+2EDRLgzHxfALATG3RuF6Vj1h1gOIvQoMqzkzOcjYTFi0HjfUMP2Qc/D7z93+Pd9wJwk24K8k/VAxAYpC29VNmQlaTW15+LPtTTJbVSVJXBrEfbaALD6SEA8p4tDZbUvn8Tzs0OGtKOGI1BJ+xJklrVnWEQ1Bg9A/X8ErVUlZQthpOvX38xfzEufiFLap+Hezy7B2qGE1JDi5TMKOwOk1fETGkIF2Ry9XPIklrpQpKygskAJ4UAEbO6E0MpA2c/IjGcmpNXaQHkWG55FOCk+YK2oVdI6jwvMLPn60+c/Qb8M+bvxlkfzv+X+0/ha8Xn8Q/q/wRmeAx87ncCyLwkMTSIgVlIZRVosy4+e760lNiqVAyIklohCxkkAMBssUWPTteLoxxwdnAiFAmA5ZRaZgG1VqkXqqkkrrx59sMLUQBO+TgAzksRGM7LRcAp8E+b34UfevR9tIsko15gOJc9nDK0fsm+Q0QP5zLDqT37hdYxnIfaojBLVbMQnHBbezg99crjwQznodAgtUZSy9V+b+G9D4Az/2z0GJYezo6b2t9HaBAA6AEbaXE9GihfeoYDwxkKLcxIamTv5zjPsTeaAed4cH9UZDgrSS0tMI+ViopYiE33pvJh30P4k6OiUdVDlBark/XQMszla9uiaCmCbQNpHipCg/LnJEupzW8/tg8tMZzsPwU9y9FjyPfiPfQhn43s2vl7ALSnMIDt7RDYdhbOo+yrSsNDRhn8LI063tvL+5D3oW3uA51v6Sc4iBnDuQ9A5UMS4OR2PJ4YbHWqhzNTINynpBYAvuHNB/h5Bpz8fK3dz6aHM5x/6/dLiJ3QUBng7LyBmzGc+yW1X3q2Ra8kXjq/ezeLv1LjBeAEMqaNUmrZw6m75Ova48N6rhhwppRaOLs+NKiKhb/LkMxOeQdlrnGNsIj+0rMten385fb6LHgGfclwGsWLc5IfRoZz4TuabVHIM5IznLYtqX3mCGD99H8BANAURCPcFGQ/IoDOjbRNhtN7H8CIzCS1NcPJLNEJLyaebGYyEga31Ifz4/JdiAdvHkyZ5dCgD27CPbnzHaQbYTkl9ARJreqCvzCEBqWQAgaVFhJKCCiJCDjjdeDrt9a/Gb4QADCYK/hKhlt7OEG957hKytdVE4Mp3RQm6ZmHMzQaDwcyFaFB7NfzxKyOspSB+7EMwFEDhQfRPc2g0R+TCMztauh3g59tJcOZ3fP8rG5IuvrO5lP4jPhF/Eb13+HmW38vQJ7l1IeT7uUsXCcwnI0gk6p4pJXAVmaAs2NVh0QdhCKmW2x9H+/P9IPs70oXct66Dye/XOEsJq/QKRV9tMhShIvNexulflM2F6vHJcN5wT+qzrkQoeLOVXdWCAhXAc4DbVFKXxVJ0vRA7Hzu4eQ2LhpeKnR+Kn5n3wjM8qGUWmYHq0WqkCFgq+ov54kt4dj9qCo5EBpUnIeFc5KKHj4ASZhqvm8xnB69WAoNOl1SuxEmWAby1lpCxaAnn0lqQ5+/iuGk/ebFuHLmoC0mqVhqhpOSio9kOPmc51YTZqyDPNiWnj/+f/RwOmgl0ClR3pPg3SS2vUipldiypLYAnBWYdhawO6C/CECpwXAueziDj1g4AwOZ+peaDy80KH8G7oPhLGXqp28vPTMBZLQktRAyqilmbKOo3s+NkVqnLDCcUVJrm6FBam1KreqpDyfZOjyHBt0Dw3nPEOXrXn+An2PAyXPy2vmmYDhLKb49kMobJLUZ4MRUFLIFA8490/6Xnm3x2sPhToWOv9LjBeAE4ksmvoRj8EYH2R9mOK/kYwChsncRU2otpa2uAZz35+EUArA+MBOdeY4rnwDnSROAHrARY5n6ByTgQSyRIw/n4stVyqySnUAGUDKchoBrvjC76BWuqFcgfvKPAQDOfPhe4SZM/J2qx5kIEtR6hIUQ7V/sP1VXpPc3fd83mOGcTQaZv2eyDh8T7x6U0wLJw8kM54guJCbyy/mEPpxqCJLa29EUKYfRgwUJIUQqWiBj3dQJgJOO/aG4wShLgMyA81FkOEMyIy+QWFKrFTF1JKmtvdRKCux4UWR2UFloUASclI47ig26PCSGZa/0jCs+NmJB3cSV9+MZTpbl6jVtVRoMJ7cV2BBT8N75p9AJi2s/AN/1+9LvshfI1wynhiPwUQ9ZMZxKCtwWgDNJG4W3RW8wYbbYYpgvKJsM5/4+nKAeh1KKJGdeZDjT/MNx8s/8GbrzRwCCh/O96xGXEXDOn2GtRCwISSkxeTVjOP0BhlMIMVsECt1TW5RcUpuxd0KHVkZYt0gNHs5DwRDtNN0g36V5rGA4ySNNFXTPbVEOyeOLHrHt5yCGBvng4+pgSxk6byM7Jus8+io0KAKOUxdUuscgbJTURtkhNaZn5QyH9BUL2lrJkTGcB1NqI6CunjV7V4az8nAKlUCbT30b4/5FD2focbrEcLIvu2A4lYiSWpb2KyFgfCWpHa/D/7vzIAVthQYtejh1LDRZKGjyirP94MPow9luZXH6yIOW7kIQxKA+a/YCzhSCVj/nlfe4MWaS62pwoUS58BxoKYr5ZO35kkpTbgE9zy54OE8NDeKwol7YO4H61vj6Nx/i1tJ8c2wfzhbgRAL1ch/bLDooApwupt9nazh5OKX2i8+2eOPhV66cFngBOMOogA8nPuquj5XwfS+Nax0WPYHh5NAgA9EIOWmOe/RwxpRa76DNDa4RbtD3b6Y5K7Fm6A0GTDMwGdsiTKERfGA47X52kBchVUpt3r/MxRYKmYdz0Lj29KD94p8FgLCAMyMkM5wAoDpspMPOzGWExpLkV3bLDGesSB9/niJzMgOc/MLOPJyPPnZweyypjQwnOmg/wk8nyDx5VyhBNUhqs0bTtaRW7JHUrg0Myn7nIW5wgxIgP9uGc/1gk65d3jxauJBSq6WAERqSJLX1cyjyYAs7FqmQ3AKDvaOjGND5jOGMHs4ANLuug/UCgiW15nQPpzBbwDPbc+C55gVm5uHstYw+LAB4ev41AIA/ZP8GXD56NR0/y9BYzsSLXsGhQXPgouHighoI7MZNBji7yHAqKPiYPggA0m6xJW9tPvJnRpB/dO7hTDIwCR+9XEC6BksMp8zmUmY4n+ECWmtYdYZzsYV1Hucs9W2c806lKrSIUuwScMaU30UPZ5K5xaRgHdpxFP2EHXs2FXyRbnh4jvcMyPeNeE2q6wAZFzb5NQ6S2hTK5VjedRBwZudh6bN0Tr1zGCnUrPhsxqTwsM6ji4CT3wf7F8gHh+oxiIkktRZzSW0oZLIqIIQ4yfI4Vclw6hUptWLRw9lOTD40mpJaDg2SihqKpHdkZO6y5+0HxB/H3/vlf77p4Yz7lT2znUweTi6uS9kIDaL3fUqpnYcGjegw6IaHUypoH9ZF1ssk3ad32r4+hqcOcU+MZBz3JamN87YN57GhDivUFC2vNpbZy/CZVHBp7gMdi/QmSmoLD+fK8yXpOhoO3fQO3t+F4Uxzx31Lar/u9Qewno772D6c2b7EljEyZzj3gH/ZxRT+0bqwLqjmSAnftu7/hT8I/HNfhX/zCz+A/8vbfxvw9k+s299fgeMF4AQyFmos/q90F1mPfYDzRj8GEKR9572KgRnSu3UptffYFkVJERd7nb3GDRJA6E6pOFFoUC1zVQMDztSzUONAD0s+zip6vsVw1h5OBs6Ax3NibTE+h3RTbFQN1WOQbYZzco7CLBLDOZOtLbQaWDOYOVmS1AofPF4XuAXOXjq4Pe7p9D4BTqcGdH6C4wX5CQyn6ELx4Ho7FeeYr5nLUmpdDThPktQG4NIJi2e2BG3PbicMWkbJKDc756Q7LiSExFxmOOd9OJUMKbUAAsOZsaCGAKcg+ekkN0XQFYMbltIqJbFDHyuffuIkzxMYTrvLFpz7F/W8wMxbvvRa4qxTcVHz9kt/FX7/9Hfi39E/AFkEVNF14mJJtshdaotSF4aUFLiReWgQSxtl0dAbAKS5xa0fZnNJsThRgeGUrBjwoCCwvC2KQ2gAT9LFfj/DKTN7AsfJP8UlhBCw3TkuEK7lkqQWCKmdea+0EWWQAwBYliYvLX6FQC+SXBZIaoMp3/ccbBSy1DUezrmUefYZZqnqlFqh4sJGNBhO9kizb04eurdb6eLVSAxnkNXpejHFipLKwxkltQxI72otUT16WNxQH854j3NoEAHMHPT7qug268Ppp8NAJUv7LMbJHs5SUutikJ6mY7FF38YUGsR9OB1+Lf57fNPNn2n24XRR7p3Os1bJw2myBOtZaFBkOENKbX73sTx5h65t3+HWPM7CQKZAqrjw/xAAZwEQ78OylG3jTpJaemYIcLbaoqAAnPXPDns4U+uUJcBJcy+SpLZgNdem1PL7yyTZ9d08nNnzec+A8+GZjvc0B06ullo32V9Wh4m9VlAvuxgctzNclEtruKAs89FfXYxf+DPwZsT/2/3V+NFXfjOwebhuf38FjheAE8gYTlq0cWsB3UGzpHaPh/O2YjijhxMrJQH3ynCS/85bDPYapsuYixMYzgBSxhkI1ANtlyqejvpn7vWrqPJlHpmdDHAmv1cJOK98As5/0n02/GF3BeXGLEk1SKpaHs7JuBWSWupleMJ1kJE5qX+QPDDGutDTVB+WRfCC/r3rcG6G4SzELEz0wlfHA06oAVJ4XO92lQcoeTilqBjOOqX2GIYzO4/vjTo2uQZCaFAMDKLta9iUUusmjD4wnJYYzq5OvwR7OHOG08Rn1ahwngUxnEZu0PsxsUMMOJnhpKRGBpwnyZeZ4bTbLDhmJcNZsI4iBgYBQN8N+DfsbwM2ZbEiBrZwD7QsNMgLOWuv4UiJkO/Tg43G22M6RmY4Qe0kTBaGo2xIqZ01ua4YTi9UDL6xLkjG8mQ/CQ/hUgsb1e9nOHNJrSFJLbej8t0FzkW4VudRDTw/5//rv+Wz+D2/7qvi36cGw+kPMJz5A86LRlbBsASbNkSHqgumcRXgZEC+7zPcMH7m7RLQ4HY+OeAkhpNbF3Drr0OsUh7ks7CiivvgLKaJ/KNFIEbbwzljOLmF1KnSRz2gBzGc+btXysAoICyyywUtF0EE8gTu2KvTT4eLxrHXcnXNuAh0KsNJ14hbjoWerhwalLVFqTycxnpsxIjOjwttUejeqTyc3BaF56GC4bRzhrP2cHJBaPShf/Lse0nazH7smIbN8+yHwXDm99I9SGqL5/cu2+NWZNZGSe0sAEyo0O8XcxYuFlP27MOhJNt8juM2Jqe0feHniRn52IfzRIYz7/9535LaQau4tjlaUlswnKWkORzvPoazj8Fxu2lCJ2zKLQgbDJ9rFIgxXsNdvoZ/fPzd+Auf/Z8DD95Yt7+/AscLwAmkqqad4L2PPf1010fAue+lcds9BsBSkpC+JqgtyrqU2vv0cDLD6TDYG4zyHI8p1eoUTb3oNuiFRS+mQh7cbxhwJobzoKQ2Vo+r/x9gOC8HlTGcwH/lviX8YXdVeTg7DNK2JbWUoutV11wAhb+z7+oOktolhtNZTNYT4DwMYOrQoOEsLMi51c2h0KH2TobvHbc3e1Nqiz6c8d6kc3xCaBAAPLM9fvH91PLi2a2JLVGAsMjqRAoNUm6EETowWNCQPgDOeWhQKanVWZItM5xyQwynYhaN9oPAjeCUWhl8TJJfROzvW9sGBojFBGnHJEM78Pu8OM8B56BVYn+RvJwPNuU8xKxA7K2XgVwHNZONG1Ii5IDse77mZfzQ22mx3HWpLYqEK9JXlb1tejjz514oPfNw5p7hKB/KGM6OAKedlgBnktTyPXAlwhzkuovIcJ7rKogmG7/5s2/iM68/iH+fWgynm7OD5Y7kwDpJasO+5wyniZ8pzs0aD6doS6GLz0SGc+7tYg9nuTjmFGgqTEQP5zqGc9/nYgCK9zB8/QoPZyn5BOrQIFUdy4nLEtWjw4Tt5KAKCbeKrDSkLkCIz8GkVNm7iQAnzOEchqUCZuzjeyTgpPvJUVsUS0VY7sOpK0ltXJRHhtNjEBO0H9sezniPZ5La3MPJbVFEllLLz8lIgLO7mHk4gQMMp0yhQRYSHXvFWRnwoUhqj5eIrt3e3RjOVCRgG9Gc4cz9ogsFvj0M4CEPZ1F4iQzn8QwuJ1lbJmyoLcrJfTiLgtD9QpRey2TjYIZzbeGgNY9HwLm/76hXfUwJH3e07iiKcgTaW/2Xx2tM1Kf69Rcezo/AiKlYFjvjkodTd9AsHd0ji9sVgFOFB91basOxxsOZ9Ti8h8FtUQZ3g606x5NzkjaewHBymMcZdsX+9WdhEe/GxHDqfX04gYaHkxbLmYfTusCU5qzAea9xgwEeAtuXvg6f96+Ez26voPxUMpxYkNRaF5oof0iSWvayzDycMY3OYDImSClWMJwMYFlSe34WFteczrtmG/ONht8Zt9tS4hh7OaaUWudrhpOu3VGhQemZucGAP/8LH8S/P72dUmAQEEEZNzsPKbUs8VIQzlCVv7y/QluUJKmNsmkAllhgNQSQMXFwEbdDqeTJiloDMOB07C06KqWWWFW7SwvOQ0mgkdlJn/t7v/er8L/4/m+If2fGoGCFkbwkPno40z3sGsAlFYbSd/36z7yKd0y6n3Jpo0IpqVV2i1vf75XUCtVRe448pTZn1EURHgIAmmTN426hDydsZJoMSWqvBIHH/gLnBDjPGHCuWKiMosVwlnLZeuQFRMFMEDOchaSW2TtVLuJWFRXp/OwbfF2rw/SQIQGx/i7qc8sAhG0MQh9iOEu/fXNvmQX1DtPIbFX5eVv5ieM8n+2nqKwWR49sUVeEBhUgQUG1GE76WfJw0prAT4eLxjEU6X49nHyN2K4CaunFktq6YJgDzg2m4D+1ZrZ97peaFyt0w8NZ9uGk7bDChjycRVsUOk879G2Gk/tKegcLhb6neZXb0H3IoUH3wXCWktM7bE/xO9fA+cpP3Ni+nHnm1ewz9fAVKJqN7FicD/23Tzk+9nDGtoKeQoNOBJzF+uueJbUF4Dy2D2feFqVimN0BgO1VCEX03mNiwJkTDyL54GdjfI6dCO/HF6FBH4VBL1MtAuCEm2C8hFIS3XCY4bwaXoP1Au/6B+g1pWo6C3HI0xi///4ktQBN/N5i424wqnM8ubg74DzHrpi8h/MAOG9vAgAyUaq3z8Op2//PWAZuryIKhlPDQ2I7vIL3Xvvu6OE0t8+ChzNjOHu+htUI6YkkyVxcIHBo0PGTXB5GUoz4XSYF/hzFcE6QIjGc3XQVPnBCaBCzouPuljxAtCBjeQ8lhopcUlvJn08JDQJC39YfygBnLanlfoDcH1Bl19WJwHDm7GX8ijyl1k5hUqffu+me4Nb30OfB82C5lQ/Jwrj9CYNoIQRGkQCnjwzn8ZJaaXbJm3zAw8mANj+2b/3kS/j+b34z/p3Zzoc1w5kVNMJG8rYooYVCPoxztHhN9/iv+9pXYkqt9SIrRISwlTx9VdsttmKYv1zr0CCho5w3SmqzRRL34WRJbU+Ac9reNM+Ryop3LJm+Zt9pf4ELQYBTLTOc9TDQUEeGBhXPN7fOIMBpxwxw0rFLqYt3x3qGc11oUCtMJMlHS/9l7uFMktqVHs49RRORLZa4xZWoijQWCjLzOBrn0Mu2h/MufThZtqazd1EN+JseTvpZBJwZw3nwfdBo+xL+fpqHkxkjn0lqY5FIaihBzxMxirWH0zqHgYoOdUEFSGqI/LxoJfCeD/PkFfUVlyIHnLQdKtZxH84iNIj+PEK326LILqQF++DhZK84Psy2KEVg1z14OI9UKywNLlZ55xLImIUG7fmuVYCTCy7t85oziQ4CSp0mqVVVqrInD+fMdrF2FFaA+wWcQ5PhXHnfFT1K2+qwpeFlhw4GxnlMI4cVpnUF31ez3vAAMF7jhhR+bzx6ATi/8kcWk74zbGpX0FKgo4XQvgXM7eYN/Kbxn8Mfx3dASRF7oQWG85fXwwmEmHRtd+gxYVQXGeA8vuLEgFMLV7w4zxhwXj8DkIUG7TuGpZRaVzGcjdAgAPgj3/7v4C9+/f8Iz8GA8ymUN0VoUI9pQVLrEkNGE3Htb0uL9RMYziiprX+QJLXRn7bKwxk29N71iMtBoyfJodwR4DwhNIi/dxpvCQCE75C1pDYDnKkP590ktWcXD/AXcsB5O6UenAAEJ92RD075EUakdiHSGwzCwMtyISsFEsNpd9BZSu2ffem34reMvx8dqRSsLhnO6OHIrseIHqoCnLI7nuFUbosptlU5ADgVp8IuPzsJcJbbqj2csXgjieGsFsHOYebhvBw0PvVm8IXYqrqs4IukS+222IlGL7Ds71L1QY5btEVx6YVNHk5kPQ6Z4TRLDGeWOsqhQTeSGc7LUBADcBZVmYfn0iCpLRkg3whUKX6esw6yBJx5qqiLklVd7Msan1oAQYcYzraHM0+2LHoGUp/bKLEkMHM4NIif/z0Mp0oMpxm5el9ut+4Ja51HFxlOXWznZOZI9dAEsEqGs2Im8gVtxX7GPpy0Tz2mw+/wxdCglR7uenNcgKL5x9rwbhWylGfPWC66dyfrYxueuqACpLmilNRK/CX/Sfyg/JfwE/rrAXARNXjo47ySFelmgBMS1gtI3TUTXL0MDKeg5N++L0OD5CG2/YQhc8B5H/LM+5LUxnnbpKCYPQznbE2SzaVLI727FyS12XPhENRN8gSGM4Zc8T3i7yapva9z3Bpaivg8cw/m1WnDrZTaLC147/GqHj1CL3ZDDKfM13CZp3c2ds9DOzS8kNR+NAa9dDVC4IxwEwxCQuT5WVisvvL4cvHXOyXxU/7jsWIXJLUueDjXsGV3lRJVw0FisMQ86ku8fEnHd0LFKYZ5AMUDd34RFntbYjh5Ibv3eGceTlpo2JLhlBXgPKfwlC/pN/Hu2McWKeb2CspNWa/IPjCcWWjQ1XbCz717jYn6w0F1abKuK9Lcv+4uKbULDKdwNgM4h8Gijm1RJjzYdHFB7nfP6AtPCQ0K94HZ3hYAwEdZSAgNylNq47k4KTQoLVIfPnyEH/n80+jRfLY1eHiWFhgchc7BK4G5TmE62rHBv1yUaCUxcWiQ2SWfLgDRneFn/ZtR3uUqhlPaeQFgFH1iBaK36Pi2KMqNETwfBJzMaOxZ1PMx1B5OlqElwJlkiiG4p2I4rYUWbgZ8vuXXfBIAosQ17LiEgsNoCKR4j95tMYnGSy9f1CsdAosINHHsf96HU1JKLbOWXBQwYxtwiqwPsIuAM8zJor/ApQi/t1FVEM2eMYkOytcMZ2Im2zuSPd8sPaSiXC6ptXE7JaO2SiImZWA+9rCcycO5hxWpJLUqT6mNDOfKPpxrPJzORtBdM6dOyOJetH4OOOP/75BSyy1hilT1fHtSFYvYAnBKmUKD2J8LjzKLtTHyomI+oo/3OCDFzBNbTQLDSe/EnJ1d8HBa5yPDqVzGusdfLPvIAkmh82PmY1G+yUVUJ3SyB5j0DqsltV7IYCtaKNYICq4S3sFAYYiS2vbcfi/jnsFLAcjuINGNMnTrUpFrj4dzxs627u1qHAwNysN5OGW1+J6VQIyJA0qpDZLa00OD0Cqq3NMQQkDS/spjPdZFSi3PValYv/d4VUe9mj0MW3UyhlPTtdiZuQQe4zWeuQGPzroi1+ErcbwAnEC84TRYUmsi7a4JcH3i5UeLv85s1EA3g0OQkx0EYNX33yfg3JjAhE2ZpLYlczk0YrsCoHgwLy4D4BxvA+DMk/SWN1an1LKkNmM4/VxSO+jwMF/vDD64HSPDaW+fQfoETPihziW1//p/9dP4m/7lP4VntxPtHze3lkVMf9gPBpzHv/gOSWqFtzGNbxXDSS+z0TpcDjoy7YnhPEVSSwvjaQsp8j6cmaRWoEyprRecJzKcDx4+ws44fOlqB+/9nOGM0eq0UPImhldYodF77olZLpAHLTEuSGo76snIPeGipHasAGeXrseELi3SYuX9GEktM5w72Gndop4ltfvUAZHhrD2c9EwzAPEZq+IbfTitbbMu3/n1Xx1+XoWoSLiYHMzsxk7Oz0fRMFx3cLIlqU2AUwkP4ZIvkyW1dlyW1M4YTkXSv81l9HBuVBlEs2+Ea10BzkOhQbmHkxun8/XLACdLc4VSUXobtnt4DpZ03q/HRrWbx0JblJIVya4xpUBbLkgww6nXAs49ktqMZY+LqWq7NcNpbA44CdzdtfCqhyiTUyIVLWeyymL7FcOpSoYTWLHojZkA1fXiEJUjgZRseDijKqEoXtQeTmY4HXpi/HUDcDr2cGbb4mL0zrhCpaMkM5zs4aSCkN7Ao7z/PELw0NAteQY1tAgJuxYyptRyIVZ9CKFB9yWBTRu5L4aTwKCzywznvn2PKal7ZJwHgoXyohr3kZSnHB9nJvC7xbmDnsa940P0cAKJSZfudA9n9NTS+Y99TJeG6sPa1NooqVXZuoPJqu1umv/u+BwfmP4r3r8JvACcYURJrcV24hQ1url4sblnMkwLW1qkk6Q2MJx/BSS1UJHhtN0lnlyEYzil4pQznLmc58EDApzbECIQpbBr2qLEhQVVmnySelnnaDv5ZCtw3itc7wye3k4xsdbtrqC9KRhODYPtlF78712PeL4z+GM/9iXqD0eTI9Q8NMjNK79rRwwNmqXUsr/HZIzaeoYTAC43GgMtyDUVEk5iOGlhbKZtwSLHXo5ZSu2M4TylD2fGJpxfBHDwxae3uJ0C01J4ODnpM3o4xwg4ndAYuH9mdX8FwJlJamEjU5gKQXR8vO8cGsS+JJ2OaRR9BCF+wY+2d9C11W6Eib0O9z/XUbK75/kfFlJq81AqAIm1FyG8TFb3OIcy1Yv6r/v4qwjNJEqGTOWAk85bm+HMJbUdIGSRUivhZzIw4afk4SQliR3bKbUSycPJsupbFeYgOVzighbYvaR00hUyKSM6qCqllj00coGlKY4zsv8EOLO2KNYmf5DI7tk1fiEpg+T46W1j8cH7yexnQ1Kbviv/c5DUzhjOtYBzn6Q28xDy81u3Eig/WxoAAJB4SURBVKr9xNZ56Dqltmo1cPRQfXymC4azYnpLljBnrJOk9qikzKyoWIxYvDgi5RpZAYMBp3WhPUYeeIcM6M88nB4De1lzBv9H/h/AdJs8nNlxsd3GuFImq4QghrNSfeiBJLVp88xwLhW2i0KuUFC0yBZmnRLklHF8YNf+kYf33AnAZm0wUtDbsqR2tiZpFFNm44CkNj83DsFKU3x2NeBktja1RQkezlMZzuzZu49WNvXmab4+PqV27sXn33V+P8MpCHBO1sckdpUznIQdxqnNcL43dXj9K9y/CbwAnGFwaBCzY87A8MM6PABe/Xrg1W9Y/HWeYDkK3AsFQb2yitj1xe+/o5SoGk5IbCLgvMDLF3eQ1GYAI5+gHl5ewnkBQ4DTeQ8tDrRFWUipzfsvWhfkd3XV6XLQuB4tnt5MsFC48QM8pdTayHD26HzJcN4SS/Cf/NAXQu8jrh5nbRviuIOk9mBbFG8zgLMipTYHnIPGsAnX4dwRA3QHhrPHVDBOvAi2VKULvVw5kIKu1fAAeOXrgNc/e9x30rN18SAAzi98sI0L6Tyltk66U94UHs4BbYZz06nIcLppSwuz8Bl+LjfEcPro4QznULktHETBxBrRJ1bAMltzIsPJ4O6AJDf66PYsuJilrT2csUrNwNJnDKeQRVALADjTZjiFlBj1gxJoCWY4CRjQeYtpv+UG0j7p4OFUSCm1QpShQQCgMkntZuhhvFxsi5J7OL88fBJf9C/hi32QAavNg9AGAgaD8qsLd0Z0UYLJg/ugLRYJGm1RUHnugFTtF0qXftAlIJsNqcJ5f7YHcEZZZD1XFYvUnOFUkMLD8IKGgdmheaQC1c2P0JznvYuSeFUznKJUlARJbek1jYDj1Pdgdw5B7ZOKomVRvFTF34u5/q1vBd6g+a1oGXFgf2IBpXyf+FPaKiFTPLCkNlcliHy/SpYl78PZIXx370c454F3fxr4v/99wF/6I6mwmt2LeQ/BAnBKEd6vtvJw6s3Mw/mz8lP4Ifc1UelVj/z7nFCx3yJ76RaLPHcZ+0DbSZs7AZA1Rpy3nYnqlP2Ac0lSu8fDKef3f7mJXFIrg6K8OL6VgDH2jaX7lNoB7utLuXfI8h1034PnJrbOrGY4s8+lXqFMMokoQW8NoYPda5xsDJcrAWfYp91UzfkmtFd7e9R4/cEJJMOvsPEhiOa/Agcn0onQw3GThVlAdcA/9Gf2/npkUjLAKb2B9DL1Mdz7/ffNcFIKJJjhZEnt8RUnPaTFZV6hfHTe4wYDzC4sQmN0+75jqI8zY5Yn67DpFAwxnPUkcDFoXO8MZ2UElnNHbVG4gqx76Co06JbYzrevdtCDTZNjU1J7WsgDgDjZzObo6O8xqb/jCgCTV4kvNxobYoAekFftNA9n+J2BAGd8WWUptYMME2cMDeJzoXvgH/5vTvjODrA7PHwQJOlffLrFs9twnnPwFD2cVO3WfozMtRc67C9vLxu5pNbtriGRXrQ1w4mK4VR2xIgem+yiTSIFj0RJbXfEuWY/uJuivPAQi6RXeDi5l+4rl+W+cMU9yrKy4CtHha98pHTS+T1+/uClJJlDeBFLjDOG06j9Hk6lu1h0A5Ivu64KSz/FBf+mU9ihg1tkOBNj9c7Zp/Ddu38V39U/Cdvrg5fzUo7oDs1B2WgBTmaKlwFn5qviRQeDsUJSmzyc+T0rVyyglNKQcHsZzhgatE9Smx1DkqwTC8FpvAcZTglAHJDUsjzQxee3LtI4lAW+kuEkiVtUvpy4UD1/CQDwGFdlYnrNcuUesdyn9jv/g/jHfOG9luGsMwGcDXqBY9NX4zWh+ScGUEmFYskmy/mb7wnjHHq6rwdMmJzDwN7/8RreX2TbCyMPFMyLpgFwqvRujL72Ac6V77v/aPhb8dPP/kZ83RLDmc9vUsc5X9h1SpBTRn4dZ8WZE8Z99fWM5965VaFBNVgWB8Bk/rMlEkBl1yl4LmVi7A5JRPNRtbe7s4ezDvK656G0BnYZw7n2O4QI5wU+nie+Du4Ad8cqqWnaxX7Nuk9zZEcF5d1YMZzUd/3tnf6KT6gFXjCcYQgBR5KjnXEQ3qTejitGApx089FiS8Gue2A+jLYoNHz/IALOUxhOkckN8xf1WaewRZ/6cMZ02X2SWmY4y+baCjayKG6B4TwnhvOD2xFKCjz3G/jd88LrB9VDE8PJkrPt5GIhQCMxnK3F+F1SaoHAci6GBnkL0QipWdxWdq0eDBoDAc5LMMN5iqQ2B5xlaigQZMacUutqwHnqoN/fnD/ARa/wS0+3eLYNE30eGhSbR5sJcBYKDk6WfeHC9soFslYSThAjQJOzV2UboFgI0hR4REyddluMomRuJtknGVr0uR3BJguBSQzQfpfkwQcYjo5ePPsW/59+9RJ/6O//bvx1X/9a+XV1AFZ2D4fQoFpSy0WVxndtHpbPrwwptSMrBsagZjANhrOQb6quZDijpLaUcCs3RYbzjABnZFCqkbdFUfRdsc1THxbQrw0mgJq1gBM6ttHgEYHY4uI3Y4Iqf7PPU2ojw9mVgGPF3KLkYYbTN4JfgD2hQapiYdnruIZ9k/qApDb5iLl3bc2c1j1hjfVBjQDcn6T2/BUAwBNxFSS1PPfWHs4VPrW8IHOwlzbvv68BJ0tFj5tDVVdKao3N3kvFttjDyYCTGE7n0dEcNogp2FVYOWB2STaevavy902OE6QICpOC4VR9fHeIDLBz8WPJw5k/B0Jm/VC5H+KHIKlFce1PBEDF5uaS5tM2RGtFb6OqYrH1SfW9+e/v24dmaFa+iex6OAoNSgDqiHMVCy4ppfZOHs57lkHXg9caKjKc668jr4tkNVcd6tXLIWpm3CVJbZaPoulZGOvQIHrnPvebr/iEWuAF4EyDEtR2U2hIfvAlkw2uDpaSWgsBe6SH834uRx7j7vuUUntKH84c2BTBIEJgJzZx8c69wvYDzhJo5v1PmUVhhrOeaC6H4OH84GbCq5cDnuMMciQPZ8aYKh9YUAawt5PFt3ziMV57MKCDiX6aJsPp7wY4pWxMsnExYqJJfRXgzLbzYKNjWnJkOO/QFqVnwCnKl5bNUmptlGvdccKniVb0F3jj0QZffHYbF9IFw5nLEnmhRV49l8vIWos3/t3dNR1P+MzDs9APLia7zRjOHaYKcJqM4RSnSGoBWDWg81MKDTrAIj28DNf2Yy8/3Pu57/n0y7P7K/bv4lYHPskU89YkPFxsh9E4j8PD4t7vuw5SOPzsu+G8Joaz4ePN5hzV9eDAIYBl8qkqzHOi8qZiOHv4JUktUrsbfjYiK5MBTjiz+vltejhdxky2RuFVLQGnsHPAqaQq5801oUEqeDifbRt+nrijvDvLrEh+DLyvNkpqJ0xeFSzH8g7pvbLQeEzeRe9q3UrIVQFWrbYoZ0N4zjb9EQWefJy/DCAAzjIVuQLhuXdtaTF+Dx7OKF8/EkipKkwv+m1lVwD/+nliWb0zJuQVIBQXjfOAofeG2aaE4zw0KJtXZpJaVB5ODp+rPJz8Zy7wzQ8sP6c6nmNhPszQoGxf7gG83J+kNhUKuTjuZ2qFfSm1bMPasw81A14NUQHOsi3KMYCTQGomqXV38XCK+znHS0PPJLXr77sEOMti/UGGs0sMJxfluhxwkp95N1ZFRgKc1/7sIxEa9EJSS4Mbs+6MhfQppXbNYKBZSmotlFfJC7pvRCnR/VyOotoyJIazX3oR7Bs5OKr2b5JDBJwmSmr3HG8lpc0ltcyiOOeabRsueo13n9/g6e2E1x9tcL09g5ieQ1ceTpbI7YxFryW2k8WTix7f/81vQv85C8PyRSEX+3CeGsWthGj2J+REXBU9nIcBTF4cuBw6nJ+H37nEHSS1BMwGUUlqud0EhQbJjOF0RwZezAZf6/4cbz7qKoazATjNFCveTswZzroPJwAoPQAO8AQ4Wbr1t3/HJ/AdX/UkA5zMcIbPaTdiFOV5NLKP7MBJDCdCiuqAEbuRpWKHZIv0HBzT75NGlDPyYt5VHs6K4Yy+0tZcs3lUAU6NM+Xxw7/4NPwDF5da915ejdcdvNBQPmc4EwCIDKefMNLC6axTeOo7+CWGM0v8VhFwMsMZJLUv99NRgHMS3ZzhpDlALfUEbAE6ZjgLwMn3jiqKJItANhtaqcOhQUtqjCV2gFsXZAynIUXDwXEAcOZFD07q1ZUMvfbMW58xnBwstgm/86lXHhzep9YgwPm6fh76VtY9hIFwTor5vX38+XVaDThrSS3Li4+W1HK7EPJwRuCqIHxjv6o+nCJLXh4wwdiS4YwJx9k7Jl8b1JJak6fUmm18f9UeTv7z0jqjSP6VCpoUYR+mpDb/zjVy9sPbywHsXSS1ZAOxNqY3z0HlsnyXP7vPfxgtUItFldLDqWQCnMcxnCwBT8F1zh/oS7l3e79cDCfN0UdcRy8kQv5dWayfFQvq76R3hB2T8ikHnHx9Z6FBDDgxvGA4P1JD6dgWRfhjGc4G4IQNVfm/IpLa7DuHCwxa4V/8wW/BD3zbx4/fWNGctgacGwhaIDq3huGsQ4NSWFNkOC1LxRoezjEwnK8/GHDlz6Cm51AwCRQVgDNs73a0OOsUftf3fAq9cHh4EdgZ1woNitKWO0hqG0+Ug4JwOeA8PHEE4Bf+fLnRODsL+/1QkKT2FPlRZDgNyZYJANCLx/rQ/FlJAevvieHka92d4Y1HG/zSB8nDmYcGpdYSUwR6UVKbp3w2FiUxEZMktVzAOe81Pvux1M5IdQNGr+B34XPa72AqhtPKIUpqhR1hvFwGHwvDygGDmDByOMAhn1xk/o+/prICnJFFkicwnJ/7u4Dv/H3p70Lhspf4i59nwBmKHb7RizWXqynVgQOHgAQ4RVUVDi1sSFLbB4m+yHyQcZ+5mEWf1TPAGRjOl7sJePengAdvzo+tMazoyxRPJO/l4kKuFeQRAUIOODmYpSsKDmuq6UppSHEgNIgoztpn5YuU4WyxnUvWAcAZTFBzC0BrZOmtrSEyho2TndcwnBolw7kqeXPfIMD5hroOklpm0IqgJ10sYpd7FHbZZw7MgYuhQcRQHjlXaz53tCB2WeJxqy1K3ZZFZq1QBowwzsViEcw2S2NPx6UrkJn/2dZ9OOk94n2JuaKkVi+cr0pSGxlOXvgfOc+uGaWc+u7L3Ryc3IuHM5PUzgIgCmXEQmFpL8O5/3nKGWWPUCyPBcxjoMGCpPbk0KAPuS1Kd2poENLaOoYGrWQ4OQfCTiN8g+FEBJw1wxnWKjd+g9cfvQgN+ugM2UXAKd0UZCQrR1en1Mqw0JOHGL/43fsrUccOR1WYGz+gp5fX7/i1J4BNoABH9YNp1QaKpDphAbFWUptCfoAAgFgC6xf64F0MCu9fT7idLF57OOAaG6jpbXSFhzNIaoEEOLcmAM5Pv3oJwAD04IcQi8rDyQuGEyutsuXhBGApLVT59aFBQPDVjMbhwaAh6Do8wE2Qfa419OeDAP+AkRjOctK0lFQXUmrvycPJ17y7wFuPBL58tcV712Giz1t8MCgLkloKy2BWJo/Tbyx8VTcAI+CpGrgExnst8RQXeHLzPhSAzu0CS58NK/pwH1sD4UaM6I4OP3BqwIAJIzOchxjSmvk/YsSiAS8iK0lt7eF0+xjOr//+euO46AV+5u1rPL2dMNw+xwbAp996bfar+fOqdA8rk4dzNA4SPjIMvM/am3h/DVpihw69nQNOS4CVwy/UgqT2jX4L/OKfBb7td8+PrTGsnHs4eQ5Y9DbukdTKjFniRaSSupSBr3gfCCnRCR+VAM2x1MIpZ2Dz/p+czs3X306YoO+F4cxZdkfXT888nAoKqXpvrJtJau/8Hjx/AgB4VT+HGm0qHKpq4V4saBcYzpz9OQg4k4olH/ZE5i6CXccptRlA9DloqxhOep+prPARPZysHMgktTmLq4t2H2VbFAuVwITZZpJaIGeI+U9LbVGKYqHUKS2UE5M/BA9noSi455Ta+wCceR/OGYtZqCmOZzhTaFD7/ssZbi688Pk6xcMZW3Mx4Dy5LcqHy3D2nQrqDgacR6Qj89paVGD+EECXsSXdbVSBdEMDcJqKBKE1zU6e4ZWLr3zA+YLhpCFUh05Y7CZ7AsNZVfZYUpv3Ats3YojOPUlq6ea9xmbZT7F25B7O6sXp9Bk09Ud0fk1oUAdApImfpHk9ptQWZYnh7DWe78KE9vqDDa79GbS5hsYUpZdQfUwe21E67e3osOkVLdB8kpZVIRbhIFiOeDrD2YrGdgj3Q0w/XcFwAkBH27rc6HgdNmKCPVXmSt/LKbURrNSS2rwP510XAcxq9+d449EZnAd+6u3nOO9VIRsues/RhMzy2eKF2dif8ALRcXJeYmM6JfHUX8Lfvg8gJOHWDKeJiaNbCDthgtobd94aTvUhHXJkD+ghhvNwH87FX6WXpcsktQ4SkLII7uFxOBQnG1Lhgj72I59/ip/5wtsAgG/7dINBzFNquw5e6jAfANgS4Ix+QZqfOqSUWiEEJtGlJOdscDGLCw9zhjNIan/nG58PTM4nv/vwsYH8ujAx3RNA1odzYdHcAnR8/WwCiJHpU6oAL6taPwiJTmJ/Sm38aLWfheQvVwZwQYfYMmeOk9TuuTcju+0Sw5kHYgDz+Tak1JahQc1U2WOG6oDhEV4Rz6k9Et9bJbNWMpwL/rbimT38Dg2As5TD+Sw46pgRP28rhlN1bW9pTDylIofNGU6W1LKHcxfl2Isptbkvcy/DWXk4aXeWQoNKabOOyZzMyH4YktqSkbw7eJH3JqlN1yy1RanUCnvaokTAsw/0ivL9Xo9c6s1pzVExcwzgjOFPeVuUX7kptb2SsFCQ/siUWiQmM6Yfc2jQgeJDZDjHMQLOvC0KP8NLoUGXDx8dvQ75lTheAE4aQnWxD6f05ijA2deSWhli7Yvggn1DKhRA7I6Dm7c/95vTfJv5KBjO8oXg9Rk6ApzWhfCfvRU32ZWAgf48CIORACcbz2vfy8WQ/v76ow2ucIZ+uqI008Q0SG8g4BLDOdnQh5FfmDQ5Bn/bkqT2tHMmZTtK3AkFeJcBzvUMJxD6cOaeTdvwMa7bIAN8U7Sp4IVADA0S9xgaFCW1F3iTYr1/4otXs36SqssYmEpSm8fpi0Y/wE2nMIkuAc6FBV6nAsPpbz8AAPR+B1MznJzAanYQdsQIfTLDOS0kds5G5Wk+amTx+gCoWJaAnaTFzJ/+6Xfxv/vPfyKGuqxKzhQKZzoc+w//4lP87BffAQB881e3AGe2YNV9+G44OOdDEQ8+SZNzSW02XxjRLwJOVTCcBFh5biOG8/IX/nj4+ye/5/CxAbCiC0y/Sy957w2MX+4hl3t1IjBohQbFfp5dMZet8vMR4GTpeXM/+HrXWQMLoUEJcCYP57T23pYa+/pwRm+ct9EjqmeS2lJRYn1DUruit+DBcfEyXhbPwu5EAJuHr+hqQbsgN8xB6Yr3crBNLLQgOraQFBnO8PsRuFbAP/W1peOjwklU0iALDYqAcxuZUJkde36/zzycyAHnCg/nCoZTSAUtZbAsuJU9YU8YZWDXPQDOewq0YXDtnUt+7OpdmwOhpbYoe2XCMRukfdxKzY+FC20nSWptktRa3MHDma0/7uOa1WPoguEtBsYd8R0MLJkdzov1+wbPh8bsUpp5noWw6OEMkto3Xn559T7+Sh4vACcPlUtqbeEbOzRmklqhoCLDuWI73flq1mvN4IfiOc6W/RRrh+qSvKKusvXn6P0OznlKqZ23MylGfw7kbVaEgJM9OhhMHBq0x8PJ47UHA679Jvo1HQOwLISIAecP2D+K3/vjvzdJgqIvcO5vg68WQEcOJRYktQh9WWMYzVqGkwHnRgNKx0nYnQo4pYIXGoMYC7k3V85cI6V2qYfX6pGFBnEfqZ9557poiRI+Rmymm5KklhfJBxjOQUtM6CAoDGiJUei0xFN/ARDg7PwEUwXgxHNrthBuwoju6MqiVxsMYsI08kLqUGhQ6Wk+ZqiK3RDeRp+Jz3yUf/iHv4D//X/xk/j5t8NifBXrIiWU8PjUy+f44V/8AJ9/+z0AwObscv7RbHGkVQdO/bbeYzsFe0Fs9E7zUw9TzI9GDm3A6Umuzx5OomBYAcCAE+/8BPDSVwMP3jh8bMgKN1lQkXeWFkvt39nHcJaSWu5zqQqGW6xJhRUKWh6Q1Mak0ZoVydnUuYczFvScgfEr2ftukwK3Wrsb5YE+A5x1aFAZYGWdh6pCg+7FWnL+Ml7GB7RZ9nDWktqsoLawBMqv2RqVksU8hI5Tag+lVDe+PPweXasEXBVEPkfQuyb3AwKVpBYTrHOZpHbX9HDmDGctqTXQmaQ2YzhRYPnDbVEKwKmhVZDr8nt8SVVwl5Fv85hwmKUhCunx6fdplGJ6m57lGsDKfN+rtVc1l7ZGVI8svMNbbHmSiJ7QFoXvf06pvcP5jgDuw5DUKkmSWrqnj7AnRQ9nnFt4zX8gNIiLNNMY0++RF1jo940p53xLeRNvvf7q6n38lTxeeDhpCNlhEA67yRLDuX5R38WU2kxSC9ts79Ec3/F7gU/9ulN2uzn4objG2d0ZTiEwoscGu5nkRXTnOMOIq62hYI8DHs7v+geAr/0NxT951ZOklvpwxrCNWlKb/v7K5YAbkRZAeWgQgJA2PIVWK98ifhJvPf9R4PmXi8/kjenjdswUprkTJ7kgR53/uxNB0jsIZlnX3Vu8CHhAYHsSPZTfng44Qed7MkFSyy8rbpmQSWqZJb+zzFuSjFpv8OajsE3j/Izh1Lmk1paS2jJsogE4ieEcKBhjCUwNxHCK7c8DCAznVc1wMgA1W0g3YvLHM5xeDRgw4ooCAFaHBp0gKZNx4ZJCg3jx4LPWJLckMf/Pf+Tz+G1YCTjpvv3mjz3Cn/iJt/H15gpeixTSVOwISYK8gtYS3BbFOo/tFFodqaoq38EWz5oVPZRrhwbJzJ4wT6m9SB8+Yh7dSvq93RUwUDKqsyQtX0Kc+SKw9HCKnCnltihKw1UL7YNDSGiB/aFBxGbVqdjF4rJoi8IptRwaFFJqV93bf8v/Ebh4Zc/uZotnWjB1/Rxw5h5H0wwN4v/f4Z11/jIeux/jHaP/5QxzOCcWkgrCCwxnsRg//D5wQkHM5OsrC0714DnOM+DMerrmHs667Qt7OPOUWjGGd2vGcHo193AKLjQ6XxRNlRQwXpUM5yYEsTnni/sveTgXZMqFUkWjU4Fp0rEn7IfAcObX7j5Cg0R5zk7eTlYojB7OPX7sJUntvrXKoc+UbWhYUssKsDuk1JKH8y4K0LCGXZ84fszodVidx8C4YyS1DOK5QBMB+v5tKJoP/SLDSe/PiuF89vQDvATgk28sz79fSeMFw8lDaQySGE4cy3BWlb1jJbUPXgc+/dedstfNwS/RK3+2KG85ZsRehdUiVQ3n2GCHp7chmEBi3s6kGA/fAr76ry33VfUUGhQm3SQfWmY4H5112MkEOH0LcBqH28niVap240s/Sp+hCRVqJqlteVuOGWqPpNY7E+RNclhdUWMm55LCddhv6O7wYvZ6WPRwWurFFSS1PKHeQ1uU/gIQAo/OOmzoGckTagFEU30uqeXrmrdmabEFGy0xQUEcktRqgQ/8JcQ2pK72fpxJal0EnEFSO0E3r+m+wefYmDbbMxvRw3lKaBCxS5xQ6U2au0hpAQRpOQD84rtX4XMrPZzwFt/y8cd4tjU4wwivz9r3bwyeIhAjNTQcjGOGM91vycNpimKCVUOxWI7/XhWzooeTi2mqSy/vlf5NALhVBDKJ8QYyhnPpmhehQbygI09QznDaFD6Uz4mrWBYh0Ul/AHA6OC/m21sIDSqeLwRwvNqf/InvBJ58zeKPmUUS3kcmrJZHhsRkbn3l4T2gRNXaJfqi7sZwPrLv0fYaAJauRfSoL6bUHiedbPV15nfZ0UU7GYAYFzDie0np8v1aS5Dpc9qVktoyNKjdFgVIz9VcUpsDzjKlNn9MYh/OVQynikoaXvgfDcxXjPz5uI+2KDljepfU21gEcTbK42f32R5JraZzqfd5wsV+wFkGY7E3kVRUR0lqGTwnwAkh7wTI2RZyH77begxahR7EPF+fIKlVVQDeQYaTPZxmTG2L8nVKlNSWc8jTp+/j1vf49OuP8FEYLwAnD9mhFxY7Y6FO9HDy/71UoaIPd/eUzxMGP6zX2Cwb+I8YDDhrWYceLnCOHZ7ejGlReCRLw/1P2cNpOfig2s5lBjgfn3cYdWI1EsPJktoAOLejxauCWjp8mareWWjQTAIVZbenXbPQFqUNOIUzGDAe5b/sZObhRJIA3oXhhN4EwCkSwymzlwyn1CZJyz2k1JIcTwiBNx9Re5cKcCbfkkmhQa0wnQbYHjqF0SdJ7VLfy05JPMMF1PgMcBY9xllPSVcwnBPGtUme+WDAOR0pqT3Bwxn7gXHwTc5wZpLa7eQgBWKQzyrAyQznx8PL7qXOQPRtaSXfQxMUtJIQIsyB1npsjYUQqe9rZDiFLSS1VvbJ55wN64P8kufSyHDm12Ugme8n1zOcN5oA5/aD9I9RUrt0zduAzoguSbSQQILSqkjfXMtwKuHxbLvs4QQcPBrYv8XAIklEfQwNOoLhPLi7ieGMfT6r59RlBT4bvYaed47+fw8ezvMnOHfPaTO8KJx7aGPrsCWG82hJ7Vwx47ndxwkFQgMV24W4zHdd3D8xcEvyF4Z996WkNng4521Raj8xKwbyIoScSWrvycOpNDolAhNGLX6ObT+1Zsg6ofiOo9jGvaXUsoez8mku+LEB4OUH4T368ScXWByN+7/c/hxwiujhPF5SKziExy8rB9YOXn98GB7OXkuY3MN5xL6mtijhmOVKhpMVH25K2RDF5E37MFWhQddXT3GNDb72tbmN5StxvACcPGJKrYP0p3k4GdwJApzBd/TLf4r55r++J4bTNKSNANBtLqCFw7Prm8zDeWxAwoBepJRav5AUe94nOd3loDGpZYazh8HO2NBCRXwQfhYZTgacaTEetxP9o6e9+BZDg6ABYjitWu/VZYbzoqdFEqe2qnWhQ60h9IAzQRXw2Esqk5lFSe09AU7ZBe8ujTeoefHDjZ5/DgiVdFtKj8vQoDbDuYOGpBY9e0ODPL2gt08xYJydS58znBSssqpXYT508HByz8O6RcRs3KEPJ/siGeDIPGFbZr657TP8jW/e4MkZLSqPYDg/+7FHEAL45IMgo29/Nmw3Jp9KDRU9nI7a8JQMZ/i9tB9ODcnnnI3EcIbj4vk2TzlGfwGcvwK8/OnDx0VjK5nhfD/+mz8EOAuGM10vK7qYeggkYCdVVxTPVqXUSgktPJ7vDIx1zY9456LnuvzdbIFdfG8NOA3MKcWU1u5GSaeHqJ7duL8Zw2lDPw1oZjjj/bo/5GTVOM/CNRqtI0TN4CwxnHmC50pJraxTag37eI+fQwPgJIYzS5YW+bb42lcezrxoE1JqHTDNGc5ZAZneN/ktkUKDTPr9BQ8n34tLRe6iH63SITQoW6ivejaOHHkw0n304czDpO7SFiUeq3fcX2Ym+c33d+bhlLr57/noKIiv6xbuv+L7mOGk98lRKbVcLOYcAXdc6FBjzBKY73EMmsKqeL4+glyK7WNi4jqdrwNrBFY5eTtB2B0Mqnc9bddUgHN7/Qw7sZlZkL5SxwvAyUP1GERgxlTWH27NiIBTly/O/kPSoB8azHBe3YeHE0nKWS9S+7OweH/+/CouClseu33D6x5DJqlNUrS2pPbxWRdaKDQZTpLUCoPt5LDb3uIlEardEXDG5NOGh3Opt93KoWXbt8D+pUFMiUFbMTolcTnoFOrDv3sHSa3oNtiA+k9FP0ICnLOU2rtG1T98E3j0ifjXNx8T4FxkOCeAgKNjuassK+P1GDqJ0WtIDg1aYBR7LfEBA87b9zH4MaXS0vAZw6moD+fRceQ6nGPLDGd34HptHoUwrYeN9NcDo1i4IADOuEAWOgLO3/r0D+IPvP8P4zd9ihaVqzycEnAOl4PGH/jbP4fPvtoB3dnCZ8mfy8mnUkILB2MtthP52VsppHka6B7Amf++qiW1QLjHvvY3rJarA8BWzyW1hxjOYhGY3YtWdrElE5AxnKoMDVqbUqtEWIReLbKcvu2TykOD9jKcQVJ7dDGlubvJRywWZGp5KrihBbaq26KI6v+njPPkdYqhQQXgpOLdgXYGnJpNv3Twa4Okti5gsjfx+MWihY4Mp89Cg/JrmiTqHNri4L0vnqFBEMPJxThzm1JRa5mmZLlgKamdoGKQW81wFrJJzvBaKHIXIVYUGpRLN49dO6wZJcN597VQHtJ1F/atYDj9Qjp+UTyqvkseBmSvPgzFwVceLAd+Gc/3EAdQ7X8umiPKg3NJ7d3mFWYSPzyGU6UezKdIahXPLUlNtG8w4HRmDOoSUd3rC21RptsrWL2Hxf4KGy9Cg3gMD3CJn8XO2KMZzp5aB0RwRzfPIKa7vTxPHSyp9Zu7p9QiMZz1pLc5DzT/zfUVXD+EFiVHAhRBoUE3hqp8rt27jAHno/Pw75POJAaq9JiGlFqL6VkICvIQEO/9ZfoMm+LlYo/CU1m9h5tuDqSQEnEHTEfJYTUBzrgdAkP+LoBT9biQBDjZw8mLMJ/14fTVYubU8Zv/2Vj5BBBbo8wqdjFafQRuggdr1z8O/1ZUxhttUbTC1usY2rEkYespNAgAcPMutHBwVQCO16ktivSB4Tx2CJLUuujhXAE4/6c/BmweH/9dmZzOe18ATi9V6F/pPS7sU2z8Fr/t5j8GALz5ZIVER8jImvz2z30M+NFxEXCKQlIr4j1lrcV2LCVjZS+7jEnSG3SYZuYw51D0+J314QSA3/kfHP3c3qqH4Q+5pNab2I+2PfLFeJoPrejSAgYZ46x1aQ9Ys7gREppkhk9vJ7x00bh/qNcdaiZiIWik6HMLQPqQUnsfDGdcyHsLWIMRGn2jp6BAyXCyvDt5ONl7fBdJbWI4RYvh5L61BxjOsi3KWoazzgQwsF7MiqdrBiebA6k3tdIdhMuBMJ83OtcueKY5nM7qCww22F3yPpxRelvtF2dR5AW2TgmMXgN8b2cMp1v0cC4c70xSK7O0YNxdTdMY+ZplHxu4dhSA/w6gKp77fSm1uaR2yd+551mJSq09a9DwHKSsEa054+IYSW3Yvoyhafcgqf2QGU6bS2CP2FcfgTB7TFlSu38bseemGSHtOAeckeFMc4j3Hn73HLh4ATg/emPzCBf+JjCcRzKTDOrOu+rFWf/5l2mwpO75PTGclpgmWVUgNxeBIbi5voJVT9AJC3Ps8eq+8HC62Hi9ZjjD3x8ToLNdegibktrJwT77IgDg+sk34vK9kuEMScJlKAfLeU+tqv2Bv+NzzfPthIJCaA1xjBy2kyIGBgFIMdor+3g2h97gnHytPFny5MlhKXlblFll9dhRAZQ3ooezuk8IVApngJt3AWSAM7vvZEOeOnQSO6/j2nupUp5Lav3VL0EA8LXEufBwGhgcD+5FF3yynC7ZdSsq9+dPjv6e8GV0vzkLQ60mfMYUSTg4DygbJHXdl/4CAECvCeiQqigWYLpdbI/BiznjQ389XlyaacLIUe+ifEmHX8zv71C0gjNFkSHI9ZOkNqXU5h7OB4ePpxqTvgj3fCGpDT3kFr2NRShPyXAWHk669lp1sJkMchX4EBKSGM7F1igEOOvdzFmcXH6ZGE6a45yBEepOi2YeKt6DHsKFoK36qWlKahmgzVJq71dS20rrPQw4BSav0Am7d8HOwzXaosBOJ8uWrUjPXt6HU2YFQGbbIpDyIRV6oPea7R9i2JFdpdWHc4Wk9rzX2DkJTszNGU6/4OEcFtYceQqtVEEJEVt9tQKw7mEUqbL3kVKbF7nuwnDyPJCHBtWS2j0ezlV+5xVJtrH9WVwLnCCpjanKuaT2busGBnAfSh9O8nDGcYyHk4E5t6Xh83VoG9HSMEK6FuCktijWwJNy4O2rHQZ/C3320UioBV5IatMYHuLCX2NHEf6uviH2jI+/dIZ/4Qe/Bb/ps9T/rYji/uVnOPlhD30478/DWcsZ+01YvG9vnyc56pEAReihSKl1Lr1c88FM36MIOBND46sG7BwahOdfAgDcvJklV/KCgxfj7J9A3pLlNGnPW4/P8MrlHAx6ERI7B0xwR/RbHTpZeh35d+/g4YQecC6SRCv/v4OEEEFSFVMcTzwXS+NN8nDWKbXxpeUm4OZd3KJP4Cbfh2ZKrQqAk8aSpLZTAk8R7hv39JfC/yvA6XXycCo3YjpiHojf323CQpVA3kGG8y6DK6y02FRZ+xAhQ+sH4xw6t8VOZuB/lbRTxcUpgBA8ssRw8guTPJzxnrIG01T1O8tBUT4/6gT282GphYbfx3CeMKRSeI6LmaQ2hGcdBpz53O5kV4S1BKmcmEtqV4U1JUnts9sFSS21HpgBxuzdk4PbOcM5wd5TvTkHPMJOc38SAuBUUVJLgCdKaqs02XtjOMtgj/BvBHBafuJsKCkOgtJ8OKHmKbXOwOwrXuwZBjoyRlwIlQsptbHA5EPRaSDLhB0eLqTUtou6/DzlAPliULh1MszL3oeWVVlKbdmHM/x/ac1Rso3EcPpU7PwwhlJ7QNsJo24lc+ooUmrXSGpnadQMOPfswwqWMHoPq5TaUyS1gooSwq/szrBnHOohepfBkto4jmE4K5VOlFgfBJycEj5CuWkeHsmA37vYQ/6nvvwc59ihP/9oJNQCLwBnGpuHOPc3mKaRPJzrb3QhBH7g1348gqICsPwVkNTyQxEktXe/xOylm/fhDIBzd/M8sYPHSmp1CA0aDbdFIflQdf7POgUhgMfnlNRaAM5aUhtCg8R1kNSOn/jetKFMZqLgYmIikIPd+71mDG4HMR0FFv8nv+Ez+Ed/89fHv0takIu7AJgsNIhfYvwSdRRlLkRaAJwaoLQ0/qqPP8I3vvkQ3/RWNYkyw2kNcPMePvAP4sIn91O3vIdDJwvp65I/Mfdw+qsAOFG3LGFQ/+f/r3g4fgnmBEmx7MI2OnODyYfU1g9tZIv9yToo5JJaHYpnDuj8iLc3X5PaEq25rhQaFMd0u+zhZAltFQBjXeiJCyC9lPM5MZdLZ3LmfDhiOEVkOMN27go4lRS4EheVpNbC+mWQIIoVdi677KDz0BhvI1Oqi5TaNQynismdT5dao3hPoUHVv8tyUc+DU1fZFyidOenebu9uKnpIN6V7IN/dLKQtMpwsqa1Dg+6YUstDRp+Vmv3bobYoISznOMBZt9kKDOfK1jPVsFkIUREalM9tVV9beAdjHTbEcLrhYfJwxtCgbdCoA7OWE5yKnrOW573G1spgdeDnMvdwYj3Dmc/LUnfQKjGc9kMKVywB4j0DzjusE+L6xvs9bVFyNcUSw7lnH1Z8xlb3OH/PKSm1XCARqLTWJwxXMa73OfpaUnuUh7MEwnxPuZWAE3YMxb567qXtSHjsJgKcbz/HBba4ePACcH70xhD8PHK6Dou2Oyy0xT1NSqcOfonem6RWtQEnLz5vb57jv/uZd+gzxzFCou7D6drVVyEEXrkc8AZ5ALuuxw5Viik91Bcq9FNV14HhdJ/4nrQhljbIUHG3GcMJ8tzdN6vnRfDSDRgTg7ZifPtXPcF3f02q2D9+GGSDLz04Xj4YhxpiaJCsJk9ehBWS2nsGnK893OCP/o//GnziSSXNlAoOIniFbt7Fu3iYFv1ZNVA2zt+mUxiRA5dlD+cz8nB6klt7VQKoaXiCH3OfAr78Y3BQ+GHxdUcfYwSc9hoG6s7AaO/IPJwxXCdbaESG0+/Cc/zX/xPAm58DHn5sxbZVXJwCCAxn3/aT8KLXgBf5tLC3JjWz5kXNgs+Qz5vnFg40+LjEjOG826JGCYErXB4VGlS8MguGM1gDeD7x1gTAqQRUlhK5WlJL4OWQpFZUC8OlUKOWh9PeUfYWvye25nEx/Xb+obmkNgBQkZjNi9dCW5u3Pnf6zmwex0Xhp14N7/R8DuM/J9n5MuBMi/E1ktpWWxRzcusZK3RKPc4AZ+4HZoYtAimS1Q9ihIeA7y4ppTZvi5I8nLPQIDXvw3k5aNxYSe2qSJabeThLhrPKsqhGzfRrKeM7577uxdl33nNo0P314eQiTZLU1tvbl1K7xsO5RqJetwdKKbXHMJz8/FPB5R4YThfXJvdvSRu0qhjOYwBnBdDXqjJ4TWlHKNdoj0c/74XBLRVof+rLz3EhtticP1y9f7/SxwvAyWMTLmpnnoegjbtUf/OGun8FPJz8Mn3uz+4lNMipdkotA84f/bkv4k/8eFjAd0c2bxZdkNSOlhZqMSl2ft7+w9/3PfgffN+nAQCbTuJaEFjgh5f281yF9jb69m285y8xPHgCPPokfZY9nEFuWADOMaSc+ntOBXNCQYkgqb2L/5KN57wwP2noARtftkVJPgRikHJJ7YeQHLg0DBQxnO/iff8gLoDK0KAGw0ltUXgs9b3slMQOffAkXxHgrM6l6AZ8//j74f5nP41/5rN/GP+h+q1HH4ek52KwN6lNyIc1Kg+nhktzF7VnMtaj9yOcPgM+8R3A7/uv4ny3dxzBcEpZLhxjaNBkkoezZmSA8trStRi3t8W2rXXQIoUGqfuS1EqBZ7gs2qLAB0ntYnqrXAKcXVE4SwynLPyy6xhOGRnOZ4sM51IfzmyBnaeC8j6wPNObeZX9xBF70XkH6RsJjAgL2JrhVN6Wi+FuA/x9/1/grW+9y85AEMvJi/QcdPCC2mL/gl3nktpVoUFyznA6e/LzHwAnMZwsgdVd8Q6OQDNTORgbPJxWDkB3Rn04XSap3aZnWtSAs8VwKtxa+ju9H/+bX7yO11AUHs7w/6U1R8FwUh9O+yEDzpLdvvt35MqrWZDPESMmKGeAs74eOSM787euATorUp+TbJyKDcxwHsNQCkGeYwPnyuC6UwcD3vuQQdejr8Oq/v/tvXm0JNlV3vvtE1PmzTvWXF3V3VU9qdVSt4buFmpJrQG1ZAnJEgIswCAsJAxGfn7YMn42kw1e2PCHjb0ePORh2cAz5nkBtoxl40EGZDCTwTIYLIHRSM/dVV13vjlExHl/nHMiTkRGRk4RkXlv7d9atW7dvJmRkXliOPt8e397qpTabBYGTRxw6rK0eABXFphHag+CDo7Q1QHnZ5/fR4d6oODkmAZxwGnQCqc72FO1JnO0g7DNdapYVZsWc7JWpXDKESm1psZuVfTxt9/9YvXYlAE2OQF8GlY4i27yV890sKbdTQPXwSH05Dep4VQ/206MXhjBP7qG5+UmWp4DnLk78xxJLhzITEot+vsYSCc156kIVcMZ6YBznmBRv3ZO06AgUThzaTTJql06EZhWsZ4H0wpAHl7DdbmapE7aE2en4LxseQ4Gdg3nqD6c+lzoe+ugfZ1Sm/suTRAziGNEkZxpsuj46rhsyaNitadKLIUzjKQypkpuhi4ESRz0BmijlzrwTrPtCU2DzH6YIMau4ewPpdTaKoEVFOlgttfNKZw592izEDF3Si0RdvMptUbhHKGeZhTFXEqtR6n5mYzDRCmdug8nEQgSrqCSlNq05jrzUtuZNmNelws44yoDTivg6fcKF6mkSFNqM21R6liQNXWcRaYpbk7BGTExFkSpCjKhwilyCqdJqZ3lGiLhQORMg4ZTak0rC902K44QxrHu9xwAnrrWZ1xqddqzfmHmPT1jQmQdVJ3ARS/Wn7+3DwD46d95Hr/+2etDzzX/G6lwWvvuOC5cJ01trCvgzPTNrKKG06loe+a1cQSJEe3YRPF1Uj0wicJZcPznSBaWTXZT8vmmO2bNHGe/HwIVpNQmAWsNvVkDTyCUs6XUbnT0PTQxwJtQERamZGgARw7SVn4GX5WIraKbKJzXdg7VXM2fwFH+mMABp0Gv+AfRvnLPm+dmXND3q0nMydqldiXqijG6GWpgrSeIf+2x2/Gu+8+rx6a9CDs+AgwwCNOJGoCxN/nAE9iTJuDMK5yq8DroXcPzcgNtzwHO6tRIK81EQAUVBuof4hBB5W55Jn03oDkDztznnAnXRyDVare5YZrPG1s3/SRombcP5xQkq/pa4TQTILNI0JfF9VCBKzIptaLENAgAet46hDaUIjer2JnzJYzUYsQsfQqFFXDWZYaRQNZkP47hIhpKpTro9tFCf7aAM6NwlpgGGUXTpNS6pi3KIO0tll8VRnYC5wZq24NeVuGMdRqoWQQsdKmdASFIuRZbKbUkI0Rl/SlHKJzSCeAhTK5jKnBV6ZR2T8eJTIN0j+D1tleSUhvpPpyjU2rJVpqcdMIDmJTaimo4TcATxej2uvD8guuT1YYqSamVkznATk0ScGbTu4F0MXicaZCtcE7eFiVn8BTP3nomIjcxYUkWCRwPjnUPTlQyPVeRcZQonLETgNyWquGMTMCp9sON9PmV++7TlNr0sRXfUX04AaC3p35ID7/7xLZ+7/S5Y2s47X13XXi2S21N10lbIavivp6tCZ1je1YadFLKnBuPzPZHGQqVHZt5BbyAGNn+m0m2wpTjYcqG9rphRaZBNdZwzqFwbqwEmddM2ocTQhsVRf0RCqeKP1YpVTjD7r7eYVY4Tx6BKsxth3sQJOer4Zy271rFmBvkoKLUUGPKM9TAWqsdt6zItOnvDG1RihXO8kMzcAX2pFH8soFYW6gaznbvGq5hU01Mcwon9AUyo3AO9rGPNqouuVMXY7XyTHOqk+pnBduAdZMh1QLANtCI4CCUohar+lFE5MCLj0C9Pbwg1xKVyazqD+COCDgd9DMptcUBeaCDm667DtHbVg/mUmpdO+CM5UilqwzXV9tcRbcyY5aRmBmfruEUiJNzx0xgDo66aNEAcEcY/ozCbosSDdQ5Pi6l1pgfWApnOBgdcNoptY5fnFJrjMTM56nKpdYRUDW93W1lual2GBFoZJCQnQTaAacHHwMMIns7Sin1rOOxSKEffhOlLK+33NEutZC6LUpuP22F01YHcs3ZhQyTOql5EUSIJOH6wREC2YPvFzt1O/mUWrveuEqMcZDl1pzsq+nDOUYhElOaBtmmSAlJDef0x2lMrko5RroI67hORuFM2loZ0yarD2csVMDZQh9hFKv6y5aa47jaPXtI4SxIqe34bmrI1tsFAHTh43ce39bPTV8/robTnj+4icKpA86azBUda1+qyDZzMm1R5tieVfc4iUvtsKHQFApnWUptbuHFXJ+mSqmFyvBwEGOvO9CmQfMGnNn7SJX4btZkcKp9zX3vNGbhyibUGVyeHAz3Ug+UitnBUaJwRr2TF3ByH06DVjg78a4Kw+dIJczUWSwg4PytlUfxuWuHOAoqKjbWQcrQZzGTz8HR7AGnU1zDOW7lu+U52ItbgGO71KqfLRGh1w/RGVzHDfFKdSO878uBnSeBs9r1VYihtijoH+BQtoYncXNiWgIEGCCaq/6yAoXT7oVmFE4ifF/4DfiD4AF8UP/tY/JRPBmewm0NLklFcLEeqnq6G1jDmsgGnOEI5SnwJlQ4XfXarpOaLlFuPMykK4y1Cc8Mx4Kjz4sOjrLmBHVApM2WYgyi4RpOADjs9dFCD3ujHGZHbtuq4TSmIyNSas2NN2/2MAgHCKMI8DCUhgQg46TqamW438um1BqFkxKFU22nipTaG7IDyBDo7wPBGkjGpaZBmVYI9rUuZ35mAk5XUE6VmqyGEzLGxopXklKrTYPy8WYmuLLTL7UaptMpHRlVl1Kra75p5wm8WnwKR7f+meHd1QGZlDJ1qY26o12P5yGXUivE8PcvJwgmjeo2yZjF5GTa4qgHw7lqOE1f18RIT3hw7DEzizy6tZPsH+iU2j5iJ4DjBQgwgDT1m+0toLudKpz5PpxJX0+rhjNw0rKAvpoA9+DhDxOFc5oazmxNsdtADWdW4Zz/eM9ub4591t+blLHVhzN7nGQWe0ctLFWUUmu0p9Sldsprq3DgIcR+NwQhnjtzoU6FM3CdrMI5zXvkvvckQ2eCeUJIHhD14SFEmJ/DuQFi4WGNjtAbKMd5MTgAAnBK7YlEr/5tSLWKN09tSeYkWUDAed27Bf84emclLVEAlS4GFCmcVQScPjwM0olaNNl2AldgX9dwilzA2XYiiME+vLiHHWdL/W3lFPDm77EuGK528EwDTjE4wAGCyk1epDAKZ39Ow596FE5HAD8ZvQVfELclf/uCuBU/Gb2l8uC7jIhcbMYvAACuy/VEGbAVzqKxCVwns2I5SuE0AcqRFXCK3ITXpJWFsU6pneFYEFqp61C3skl9GTFEqnDadXH6WD/SKbXkz6BwAkr9MzVgI9ui6FosU8OpJ5e93iAxwDE35Uzap616BCqYDfu5lNrctWVN96Zdb8/33aqUWn0zN2m1Y0yDMqlTGaVWudT2c6ZBjqCMadCkLrUYm1IrdR/O/P7Z6aN2QGz1uYVROKsKOFVq3pvDXwEBWHvTXyx4kjJpi2Vaw+lF+/VMpnIBJ1kLE0bBGZdSC6RB0CQGKMoUKWsaRPFApWfPcA1RbVb0cW9qOF0va4hmevA6LfSlA/R2Mim1wmupgNO0RGlvAgC8uFjhNKZB9rHfCVwrpVYHnNLHs7vKeC5Tw6n/O1Lh9Gyl34MnUoWztrYomd6fVaTU2orpHPdGqxRCyuI2NZnfR7rUlvXhnEDhTEze1OdyZzENAgDdgmuvG6pa5qoUzhpKeubpwzmkcJrjYYJ5vgk4fYSFokHsr6KDLroDlZrcgT5PT5DCyQGnQauBp0jL2HMEnItWOMWYC/+0GBXI9XMBp3BUX8nBYZp6N0tKraUMxCWmQTaB6+BAp9Tm+3C2RIR2/3kAwI5zungDQjnH2i611N+vSeF04WMAnyLQPCv6JtCcs4bTYCuc6mf6NDPpqNVhNUdMLrYiFXDeQOpSayucRSm1LU+gp02DYplVlGxcQfBdgT1RonDqG8ggmt00yIzTKrq1rdzbGIUzreHMqoyHR4fwKUrMjCbGrjPSDpWjFE4zLiaIMRO9bq+nVrzVDqkftmmQNVaeruEMczWcMtQpZ/q6+iVXT+Fffeg1uPfCfBkcriBsx/rzGOMgHSiO6p1oFJ0wf+t0hksDYu1S62XaokySUusAUmK95ZW61MYQBW1RrJRa+zxIFE7d57jCgJOIIEHwKcKvtt8Icer2gifpmvlYItKKjhseJu6MlbJyJnlPIPudmHtzouCUBCGpwjn+PhrTcFsUxBEGM7ZFiYULJ1fD6bhutrWIZfK2hxWgu6tSajGAdAOQ14JLMZy+qr1EaxMA4I4IOE1NtH3sd3w3NVgxNZx2C6ppajitY991XbhOWicbN2EaVIVLbcWmQRRHaV/U/HGSUTjz6bZmwaRkHyZQOM15IJOU2tkUTnI8uIiw2x2o6/28wX2tCme+hnN2hXOalNqIXMioD58GhXM46a2iQyqldvdogA5xwHly8VqIyMMm1EV1HrMUKkhlahIzSa6iJQoAvOjyWQDAufWCyabX1gGnUSGmPKQSsw09qZwwpTZwBfa0wpl83yalliJ0+ipw2fdKAs5cWxQaHOIA1QecEA5WSK8Ie3Ook1pprkzhdLIBpx1cmUlHkwFnRA425A4AqBrOJKVWjetAusUptW7ah3NQoigQEbZWvDTIQInCaUyDZrlx6u84oIIGzzUgIUDapdaxAk7zs3+krmnCH+EwO4qkoXw0VuE0alqqcKrxOOr1LYWzIACw3Pp8o3DmAs4o6mdeR0R45W1b032Wwn0m3NB9WY3CSXFcPtkyqcMFAae6jul2EVY6peM4iKRRdydVOCOstz3sjKrh1G1Rhueo9jlsr+Jr19U4BKSEi+pcaoH0+/j9K+8v3l19vY2lhBGB3cF+TQHn6JTaxBRlgho4U488iXphyiZslMJZ1tO1bHtpwJnUcAoXjnAQm2PJun7vyRWgt4sojhHQAFIrnADg9HXWVludM150pBapctdSk1Fi764yDTIpteo60l6xrp9TBJy2Ouu4LlxBiGS9NZyZFNgKVNRMAFuFaZCMLIUzu73MtWKmGk43+9wCjJJp3jv5fFPOgchx4ZIxDaqwhrMOl9q8wjlNUDuyD+f4bUTkgaIBfITF/diDNazhCN1BjN3uACuscJ5sBt4aTpFeDZyj/2A2jaP5gDMp3q/I/aa9fgYAAV7Bge+t5ALO6RVOAIhDNamcWOH0BK7LdfSkl6p2bgCAcFrewOpA2bYfjgo4SQecMptSe4hW9Sm15KINFXBOrTLZmGDRqSBoBRB4WddPO9AueqxuYstYRLnU6ou6VmoGcArXM1peagIwrmZqa8XH9SidMOXTTN18Decsp5AV1Nc1kbJJFU4JB3GSimUmLKEOOJ1pA05b4UwCzhHbMCZBRuHU14Fe306pNavWVlBkqXB+W41FZFIANUlv3orTqxwi3IhNwKlqh0lGpWoLjQg4SWdq2Cm15jmeEFO12IDjAWEXZ7zeyJRa0tun/Pmpv/9I0pAyF8JRLTH0tXrImn8OjhDgP0UP4tydryh+AqUBZ5gonAf1BJzrt6ifOl2XMirXZC61gN2jcLIazqG2KHE0sgxg/PbcJEWXrD6cjmVmZI5FQaQWX7u7SUotrIDT7atFPDulNi5oe5G41I5Jqd1YW8OV0yvJexvGpdRmUstdD0SUXB/rUjiFdQGvwoBGOCIN+CszDTIKZz6ltkSFm6SG0/xtkhrOfIu0KduiCEe3RemFIMj5gnHYpkH1pNRGs6bU5ms4k6B+AoVTmJTaQbKIbkPBGjq6LcrukZ1SyzWcJ5LQW8WmTqmdR8rP9uE8/im1uO/LgQ9+HFg9O/w3r60mo3LGlFp94slQBWRJz70xJ3DLdfDPo8fwFf3vhXCtlNoXfRleu/8fcW7wJADgKDhTvAHdFiXO13DKoHqXWuFiVadHOFWYBs2lcKavdR1jq69+zyicBY/VTWwdOzewOqRwjjQNslxqx7lCbq34eG6QBpn5BQDTimVgXGpnUjjT77iqtMUyTA1nGMVwESftQ5JWJV0dcAbTKpzpKnxqGjSqLYpOqRUmpVb97PZ6qXtnkWmQFUQGev/ifi7g1NeEqltMOYJwoyClNi659pgAL58qTW7eNChOJnPCarEx0Wr6fe8C4hCvvvFv0A/jxCbfxgv3sSfbQwqnUb2K2vGE0K02dGpkl6oz7Plg+B349sG34L5bRqQ5WxkliUtteFDPZOrK64D3/zxw8WXqrTNKkZlQj1cvkyBognN4pMIpZ1M4Y+Gq9mzI9qZ2BKXHXlISgUThtFNqTfaGlwSctsI5fHyYBepsSq2TLpbo48bz27j/8qb6jJmAs3yh2x4HE3yac62uhTnXXvyvIqXWmLQBQzWXU2Hqb6VMTIPyi0fzK5wTHOO57bi5ntyTQo4Pl5RLrbCzbGbEdFqoIg06T+A6qt+6oYIaTjlR2r0HR4bwEIIKfCaotZa0RdntDpKsOFY4TyiRt4ZTOqV2HpfaRbdFGZfaMjWuD9z6cPHf/JW5XWoBAFrh7PX1iv4ECucB2vhf8mr2hv7oh9GJ9/Ce/scwgItIt7sZQqi2KFnToEMcojWsGsyLndYzVw1ntaZByKXSZgPO4dXuuolJnXORv44QbrLibiYK4Qi1oOUJ9KVlLFSyz6c6Pp4ZqO9gIB14XvY8TxROE3DO8vGt77iplFqjcIoChTPSCqfpczkx5kYcT5BSaybylJ0o9PoDZWRkbS/bpsJKqU0UznwfTh1wVqxwCiJsy1xKrYxLA04zsRhWOHOlATLMqDZJkDDJ5ObSg8DVN+AVT/4UfAwK6zj9wR520Rmq4RQj9g/QdYbxAOiqAOTIqW4i82m6iiNnDfecH6FYGoUzttqi1JVSSwRceW1yfSu6H8tJFM5c25EyitqikIz0Ath8KbVk3VsdkxoNS+HUNZzU29MBp+q5S/o65A90wKlrOD3ZLTw+kuutdf1cCdwhl1qv1cYDl9R91f5kgtQi96j7p+uIZKJv6otN4F9bSm3GT2P++ZBaPDK1rvOk1OpjS0bpYv2QillWwzmJwjk+qyJfp5x+pikDTuEiEFKZBlWgcKJ2hVPtXwQxXfpwTtE0cxOa4PuKhIvAeHkUzOFEaw2r0AHn0YBNg046kb+WKpxzBJy2MUTVk6RJMCuUlSmcZSQptZOlwg5hVnoitZrTH+jJ1dgazvTvmQDj8kP4bOeV2MIutmkzSRvNQyI1sQAAxDFEqGo4qw6yMs6R/hwKZ86NdybslTVzUS8yDSqwyK8b8z1F7VMA0poix3HQlw76I0yD8gpnWe/MzRUPT/fUGPTgDamhZtI10Cm1s/TQa17hJJCMsd8L4SJKaqWS9KiemShOeeOynBTHtUVJ+xtmFc7eoD+UUptt3ZF+P+2W3nYupdYsZtWhcB6gpYJkrXCSjEprOPPtXwzC9SFIYjDQ9aa5wDWCUHWck15bHv0wVnrP4yudXy5sjRKEu9iRnWHhwywyFKQohnBUjbzup3gkqlMXBRHuPrc2+p5Dqg1VZLVFcQYHSf+5OskoW5QNcMomxmYyPolLrUqpHVY4RxmdjUMKN1VM7YDTaiUikppLwq5cAfV2EUaqhhNukFyHvEG2htOPRwSclmu5YcWzehzr60irtYL7L2/o906fK4hKF7lVb1P1XRqF0wT+U7fhmBDb5MepYPHfEZTs61wBLOlxjKNU4cxtL5tSO0LhLPtMObfyIoYWXsx4TO1S66AlYt0WRaKw9mUa8m1HKsQRaSr3tKnDedU4VTgnqPMWHjqkFlOLAk7yV7FKqUvtCqfUnmziYB1bicI5h0ut7SR3EhTOMkxK7RxtUQBAamOQ/qQKp/XZ3FyA8asXvwEAcJ020fZHbEfbeMemhjM8AkHiUFZfw2l/FnLnSamtWuFMJyzACIWzwSuESccMg1OZ/XEFIYRaaS9aDPAcQkh2Sm25wvlEVx1zXfhDx455rVE4Z7pvZmo4Gwg4dRuN3aMBBGK4XnaiIbUy4QdTBpzmuJ1A4TQ33nxKbVENp72YZBuJtAIffekk6fXJ54t0DVvFkw91fJGaiNs1nCUBhlFvihROAIgGPbPTmedE5JQqp0NcfQN2Tz2Ab3H+LXYPj4b+7A92sS1Xh2qs04Bz+L0iciFkCHRVANKrUOF0HcJLL5W4Bgu7hlPCQwgR9QC/BoUz/9aZNmW5ILJM/SkwuRqF1AG1DckI0cwutR5c0xbFMtKzFU5pLRgqhXMnSamF20rNy5KAcxMA4MW9wom2V6BwCrutjzYNCtoruP/SBu4828Gd59LJMNH4OUeUCzjj3AJA1dhBZhVzsUxK7ZxBVazN3qDnIHnFNKPu5d9L5ALFIsQEx3iuHji5Z0wbGjgeAhFjtxtqH4H5vhtXZx65IwSDeZH6uy1aeCkl147GHFOTfN5YeOgYL48i88hgXafUKtOgVeqqloRziF/LBgecFjJYh0Pm5D/+bVGqcqktJVgHDl+YO+AknVI7qcLZ8qwbSW7S9dSpV+O/yRfjD+XtaHujAk4n24dTt304QGtag7bx2N/JPMHiqatqErFx6+zbsNXRJOCE/rlY0yCZBJy61siaAIVwRhoCERGkUN/rQDql+7y54mM7VpOkLvykN6fBrPKHUTxzH04IN5nwNxFwmpTa3W4IFzE83e/OKIJioI5trzWtaZD+biZQOClJVTTqqnrvfr+fTsSNImMbeVgBp+cI9OGnfQPN54sG+j2qvfGa40S2NpKUWiHjiUyD8jVOQp/XYaJwhqnLKdREuygILHkjbL/0G3FFPIvoqd8f+nMw2MEOOkNhAyUT+IKAE65KzzQKp1Pdyvnfe+/L8Re+9O7RTxAOBEnEUYQoluhAB9F1pNTmMMemXbeVNpYvUzinCTjdoRpONzpCF95s1xBSJR9qR9LsISHSxQSRuNQCe1iB6O8jDEMEGKiFTX1MBqEOOHVKrT/SNCi7AGkwk2OpazjbrTY6gYtf+MtvxKN3p74O6y0Ppzrl2TfG8MgzKbXJ8VrPdTKbTTH/fEgIVFPDCRNwRpBaGR92qbXSPvNM1IczG0QWMUrhnHoSJFz4QmL/qJfdvxm5uKkWw3y3pmArMauaMgQSIhPkJ8fXRAqnn1z3ihROBLoPZ1+VUWy6fdAJSqcFgPpnQ8eJVlrvR3Mc6PaFbSEptaZ4vwmF8/SdwB/+fJoGN7VLrT7xjMIZzqBw5m7ogefga3vfiZWWj68cEXBSUlNkAk6lAh3I6lNqM59lnhrOcy8GvvvZ+falQOEsquEseqxuTEptXwectsI5gFMeTLo+IFWdZ7nC6WFHt8LoSW8o4PSSlFqlxMxkGkSEATw46CVBdJ1IEAiq7kNQDE9fu8y1RwzUsT2fadC4tig64NSf19Grsv3BAGT69hX04XRyq7c9eEl6ffL59GJW1U3AVwMdiPgbCExKLaJyw4wRLrVmUh4ZwyMZp8Y0+vnTOnH6Z64AAHp717J/CPvw4i52ZGdY4XRGr9xH5GQUzn6FCudj950vf4IxsIpCRLHEKpmAs4GUWqNmWOMqJ5hYxxOooPb2HFvhlBKr3WfxlHxgprR8KbwkgCUZIoSASwTXcjy2+3DuSn1e9vYQYIC+G6QKpwk4TUqt7OEIw4G+N+Ka73keEKnU/J70sNounht9+K334Ft6d5R+rggOQinguVmVtjY3byLEkiBo/lYdgFI4+0lK87wBJwGIk5TaoTlPkm5ccIxOUsM5RR9OGlJMpw3EXAQUYb9rFgfn+67FBOrsPEjhAfGMCmcm4Jxc4VQpter+IIrMI/Xim+ztY1euYcPpn6h0WoAVzgwUpClB86ym2w23q647moRGU2rPvEipm9c/o998NtMginqQUmIwmNw0yJCvkQk8ZXu9140ySqgN5ftwaoWzjrYomYvmPApnFdjvn/SpG1YzE+faBhXOFW0a80f7apXcBIOOoxTO0hYDlpNtWc3U5oqPAVz0RBs9+EPBaWoapBYjZjINAjAg3e6nsT6cErvdATyKE0XG3AyFUSfdaU2DClJqR2wj6W+YS6kdFNZw2im12e9nQD4ozLdFqcc06JW3qwn4jXglYxpUVrNnJhb5GknhZds7kcwGrhE5hapSGZ0N5bA9OHgh+wcdHG9jdSheGuWiC+hWGzJVOLtO/epigkn1NQGnqU9qQOEU7vAiQZpSO/qYSlXQSdSLnMJ5cA2u7OMpeWbISXgSpJO61CKOkvEUhKR3JVk1nHtQi0lOdxseRWpCq6/1rVCXCemUWvXZShTO/DVR+w7I3h568LAWFH9n6y0PFzfKrzFG6TelDEkNZ43toxKFsJI+nJQEgDTnPCFNqR3Rh9PUxRddNyZZDJmoD2cucE1U0WkDTgeeiHHYMz2T5/yuJwiWq9j+VGUO5nUFAeekNZyrWuF0vYJMABNc9vexezTAutM7UYZBAAecGUTbUjjnyJsWVtpiHUXPY99fX58aUTjP3KN+Pvcp/eZTfl79PYt4gMN+ZLVQGKdwpn8fUjitv41MqXVcCJKITBsDK6W2cqOcTErtHDWcVWAHnLkaTvtzOwWP1c3FU2ry+V+f1KYiZsWdCAO4KpgctTsmpXGMinRqRZ2bB7SKHoYVzqSGcx6FE8BA6NrkBhac0hrOEB6i5HgzAZofqWMb07bkybdFcfyRte1pSq0OOE3v1MEgVX4KnEHFUMDpgXIKJ2pyqX3xhXVstD083Wvn+nCWqQbZibLBKJyxruEUuVrQGM7Uq+mdjdMAgOjgRvYPOjjelZ3hgLNE4YzJUc6nRuF0G1w9NyYdkSpjSFJqG1jBNwqnnZook3TZEoVzgtYpCXmFc+ePAQDP4MxMrucxpTWcyvHYZAdYbVGskog9qQJOr6vVcC+t4WzlUmqB4uOjqA8ngDRFv7ePHnystmY/DyNSi8GmdYoJeKZtwzENiUJYwXtQpoazgpTaOEoDzqEazpK0z2lcakvbohQrnLdsTpsN48GjGAddHXBW5FJbl8Jp7pFTmwYNKZwmvXoChdPx0SIlqDhF5pF68Y36+7qGkwPOE41opwrnPOlbjhXwLFLhHNUPq1LO3KV+moBz2guEmyqce7rgHMDYm3yrTOG0Au22X/wdJOYapvZUO/AdyqD6usVlCjgdO+DMTjBsNc8O9prCtMh4LlYXXtdKqQ2lquEcNXkzNRGDMYrilg44d7CKrhw2DfKstihxLGc2TQqpuYBTapfa3e5A1aDnFE4vqkjhHFG/CVgBZ07h7A/CYYXT+lLdnOPygHxlJmMRx8Y0qOK2KILwqqun8PkDz3KpjUsnv0mNZG5hwzGmQdrwKB+4xjR9wCk6p9S2jvIBp/p9p7AtyuhJakSuasPQ3UYXAVBxTWwZ9vU2imOsJSm1JUZDFSEKgvCkb16p+jO5wqlcau2A8wkAwDM0og/0OISrzuU4BlkKJ4CkNjit4UwVTlcHnLbC2Y60wumtJGNeZArjJYpp9nHfV9sRA51SG8x+3ERwEUKkC30113AClkJYkVpmtjev621MAmSl1IrcsWhSpgsNfKbpw1l2jCcLGdma0FHu/qPfy4WHKFE45/6ua1c4tWnV1KnD2YDTXBsmyoKwRKxi0yA17xGDfeweheicwICTazgtHCvlRMxRw2nXJS3ENEifD3baaW20NoC1i8Bzf6DffMaU2niA/Z6thsyjcFoBZ0lKLZA2lU9qOGtoi1KZaVAVZBROU3+gfi12qW0u4DRq9+rmeeB6muLlCMLPRq/HU3QeXzbipaaRcjTmkrbVUe/xc3gjno8J/9eItihhHCOM49naogAItYmRbGBSL/XEZfdooIxGjMIpjMJ5CDiYvn44Yxp0UBpwCr+DnwlfjyfWHgSQXgPDQR+UUzjLUmpDEQwFnHW1RQGAV99xGk/8bx8y2gHFqtKyPKV2hMKpV6yzKbWWWzHE9JMbr40ePFBvJ/u4Do5VDWf2T6IkVSwmF442DTqklWbPbUqvt1GMtMdcIzWcw0F4MsZlpkFkzqMJ1Iu8aZAOOJ+lc9PurtqeCQyjPiBzAWfOzEgIwp6u4fR1wEmWwtmO9tT/hVA/+4MRpkHFWS1BkC4K9eBhdURK7SREWulPUmqnSEmclUl6rk61vSraokAvWslU4RzlRFuYUnv2HuDedwK3vGL0G9zyCuBF7wDO3TvyKaNNg6YPxFyKEMfF6cFTM0nbl7k2P2Pt8F2PJa7CgNV2Z4LPS9biqlukcOpsD2ewj93+AGvYA1rlNdHHDVY4LbxONSm1ttV/PmWsCVKFs6Fg98zdakIKzBBw6pTaqK+bBk+mcNpBZT5ADKwgMxgZcKYmFgByKbWT7/5EOEukcJaYBhW51DY6KdVj8p7X3Y+tFQ8XN1rJPvxI9B78O7xu5EsThWnMSvlq4MJzCD9y9Fb88+gxeG5O4dSDf9CLcNCLZk4pblLhjC2XWoHYUhLVsb+irdinDjjNiZAonKNfT0Lgr4R/Dk937gOQ3ojDMERgVOSC3oeOm1U4Q+HDifvZjetz1KnBsfDVd5xS/SxlDPT3dKBYEnDq4yEf0JmaHJnpw2ml1E7bFkVzQKtw8gGnTqndRmdI8S/rw2m3RTloOOA0EzwVcMapaVADKbXJtd7+TgoMrPIkCuck6pv2BEjYeQJ90cbBjL1Ok3EM+zo926oHzrWyMC61ABDogNPx2sn52o73h1pqFan4yQJf7pjyrclxDx7W5kqpVZkqSfZVAzWccYUptWp71QScEgTEaQ2nyKXTlKbUBmvA1/xzYP3i6DdYPQd87U9lzDCH9iFp/ZP7jqZddHc8uIiTbJa5hZaaTYNmTqm9683A238w+ZVoimPBiincEtMgd6BrOMMXgLUL0+3fkjP2ykFEGwD+hX7uPoCvBvARAC8G8PNSyu+vdQ8bxF3ZTP6fd0+cajtWgDFPe5VZSUyDmlA4AVXH+flf1m8+W0qtEw+yKbVjbg6ZgHMmhVOnWekef4lpkGxVnlJLS6VwFrVFGQ4uzX8XoXA+cPed+OSr70wm05O0aCHjEjqmhpOIsLni4/k9FYTlFUyz8v79/+5TOOxHePTu2VLiIq1wlpmSVEWSUnukMwRyNZwdOkIEMf01zdzs5fiUWhOYJ5NWHRw6iJHMTwtuznmFMxY+3PAw+1hNLrWAquPse3pCdnQDYkxKbZoCmEt/MxN5bXiUD1xnSakFgCNnDb7po2goUzid0ZNUSS4ceQT0drGPhgNOfR5EcYgwdhLzjCZMg1KlqEjhHG+oQhPk1Utycgrn49j2z8Ppz3YPNul3YRiC4rAwpTZjGqRrOFs9rXD67eReIyDTc1cHnkXHh3Gpzc+dgyC9Z/Xg4dScCmcEkdZwTmBsMy/JZ60s4DTf05zbEw4GYQhvlGlQUhdfY31rPm18klTdIoQLB2GSzbLspkFGUJrlmmyTeLRMcvxaCqdXWMNpFM4DhP0jtMWeWjQ4QUzybX8dgB+SUr4FwDMAvgaAI6V8DYBbiKik+dbxwrVSamkOZVJ4C06pNaZBTdRwAqlxEDCDwqkNCeLpFE7XEUkq7UwBp1lxjwtSak+0aVCRwgn90wo4F9CHM6kpWzmVUW4mUVuNzfg4hRNIjYOAtA2KwRhtOUT4h+97EO99aLaep5E+rmUDbZGSlNruAEJGaQ2nPsZX0UWfZjjuEtMg3YezROE0Q5Ock/q9HcRoJQqnmahZ6fA51TISAdy8wllTDafaF8KF83oV+Whb1VSVKZx6silzCxumhjjWPUPFUMDpTt0WBQC63jpaURpw/vWf+3387v/+PABgt0DhNJPgolSxiNzENGgfK6Xtg6rGpEyaPpyrDZoGAUAoRa4tilHbS0yDpkjrk+SomkuTbrf9OLa9czOXZ5jFoijs63pg61gyjrXmPCdgFybgvA4AcLxWtl7fyymchaZB2QVIgx1wdqWPzhwBZ0wi41KbpFofo4BzmtreUshBGIaQ+pjJ9/VMazjrO09lTi2fPaXWhSMrVDhrNg0y95LC+tgpcJK09glSaq3FfjcoCjh1PXtvD2egs1pWx7SbOmaMvXJIKX/U+vUsgK8H8Pf1778I4HUA/qjyPVsErdTAIJ/qNQ0ZhXMBKbXmJtqISy1QScDpU4jto/7ENZyACizDflQQcKavbfvF20nSVayUWgmBHrzaFM4YYiGKdwZ7EpJMWApSahdRw+kG6vix3BTtfSjbFcczNZzjj5vNFS/Zbn7Cebrj42+++yV43V1ncMfZ2SfDicLZRA0nBBDH2O+FcIK0htPcVFfQxUAEmLoD7JBp0OgtmOPFKMZmBdmhSCmcEQprOPPOs7HTgidHBZz1fJdXLl8GngWuP/NFtGRUOtkyK/dDqoNZvQ6NS21OKaUZajgBDLwNrBw9mfz+sd99Cq9ZeQb3Op3CoNK+1uRJVLjeLvZxulEH6rRmPkIUu+hQF9JbaaxPdQwaoXCWtUUxQelkKbXqjSJVQrHzBLZbj8x8/ZTa5Toa6IAzk1Kbq+EkQg8+YuGj1bcDTuXs7SJKDcOMwllwjzOLb/l9buUUznlSamM4iKRjmQbllM4akFDOslXd100AmDf5mRrhYNAfpCm1+aClJFuhKtJjvIKAU1foZrY3K00pnHPu5/qKOjcubo0397FrOAvjC7341pZHOEsnM+Cc+NsmokcAbAF4HIC5A+4CGPpGiOibiei3iei3n3/++Up2tBEC26V2HtMgK+BcQFsUc8NopA8nMF/AqVdcfQxw46APxzhaTnChMfWZQwGnlUrcGpVWXBBwDtwOAKo8yDIpWQPyp6+NqBoh0iCoLKU2URUb3LeHvhH4qh8byukyQUzZuLiJwjn+vD3V8fV2h7dHRPiGR67MFWwCQGwC+4baokSxbT6hA05hUmq7iYnRVOTbopS51JqAM6dcFKfUWt977vuRblAQcOqUWreea+ltL3kEL8hVRL/1Y1rhHD1mlCgy+cmhPu4iXcOZU0pjcgp7H44jCtaxKvcRxxK9MMKNwwGou42uu144gTZ1YEXBaCxcpYB3d7HXsMKZBJxxiDCWWMVho03Nh0ybJqrhzGYKlJGMtUk/P7yG6+75mb/jpL1NOADJKEmjBdKxtVNqASD217DSVz1bhU7ZM/2Ak8WiROEc/kzeiBrOVitdaOqTP9e8IqKcS22SNlqjaRDSViZVUFUNpxCOUvzDyDww9Hdg/qCojOGU2tkDTiHDY6dwzhvM+/qedHFzgoDTDjKLSqvcABG56NARztK2euwmTKkFEZ0C8MMAPgBVx2muQKtF25BS/iMp5UNSyofOnj1b1b7Wj9dCD9rEZh6XWqupq7OQGk71szGFc/2WdPIwq8KJENcP+hP34QTSgLospbY1IqXWLCjI2NRw7iN01YS68nmY/k4GEwRDjWAudkOmQelTnALVs3a2rgD3vWvo4aKU3zyub0yDJlE41TGX78FZJYnCWZMql4UQhhHcvBuszq5YxRFCMUNKbaJwxmMVznxKrTnmHcSWaVBBKprIK5wBPIwIOGtSiy+fP4MfD9+Gc0//ElryqLxmKjENyh1nZiKvA858Si0Jd6bJkww2sY4D7PVCPLer1FNvsIuus1Y4hRalCqcHVyqX2l10mq3htBb4olhilbrN1G9q8gGnSfGdxDRospRanaIXDYAdtR7/gnsOjjPjd6yP9cQ0qCClNnWpVY9HVsBJ7qiAUz1elKZpzt181kenFSCW+rgX/kx9Re19jyHSY8+Yt9Q4T4pJzJ06aSMrquEkRxlNHfZ1Gv5QDWf9KbVDi4BzBJwkI1AScFalcNZzjzaZIHPXxybf1/hrhLADTqdA4STCwOlgFUc4lwScJ8s0aOy3TUQ+gJ8G8B1Syi8C+O9AYhf5MgBfqG3vFsCBroWYxxHRs1bi66g7GkdiGtRUwEmknGqBmU2DfIS4cdBH25mshhNIg8nSlNpRAaeZAIWpwhk6JuCsJ6XWOJcunCTgJPvH4l1qR+DkVvKLCDwPfelM1M/tlG6Nkq/frBJpbigNtUWJI7v+OatwtmiAyJlF4dTXjwlMg8xxkgacqcKZBJxF9S75iaYbwJeD7GOxcamt51q6ueLhZ5y3oy/aEJCTtUXJ3zrNwoJuiyKQDTivnNvA2Y0pm6kDoJUtrNMRdvaP8NyeMiRak3vYp9XC86HMaCQWLnz0gcEh9tBu2KXWBGSqhrODbiMtUQwRRHYxKqcSFiGTtijj70VmO3EUAjuPAwCuu/PXcMZhHyTDzLFkPodjFFj9HqG3Bj82PXdNwOllfi9zqfWc7AKkYSVwMNBBbjzLdcQiJic7DnW7kUKdq1WmpZrvbt6AUwgHhBj7XZ0VkTvOzBylymA5T+pSa8ZhxmuC40HE6T1IzK1wTh7IzYKZ38/93U4RoJOtao4wjxy4K1ilLs7Stlpo6MzYx3dJmeTb/iCABwF8FxF9AgABeB8R/RCA9wL4d/XtXvMcCiWNz1PDaQer85gPzQolAWeD6bwmrXbaC42ekPs0wAuHA7Rz6XdlmIC6tA/niBrOxDRI2gGnWgWuPKXWBJyzpDXWgZk0UDZgtz93URC6KEaZQ9kEnsAA7kSmQVta4XRrVDil6S/biGmQA4JUtVpAcg7a7pozBZyZGs5y06DUUTirCrmIEOTO6cxkJH+9cFsI0EcYWS0mdBZCHX04AbXvq5tn8Ym1dwAAZMlEMg3ocvtizM8ShTPOrM4Hvg9/hkVMZ+UUAGB/53qicG7gANfjFRQJH6lL7fB1TwoXm1AGRLtypfp+w2WYBb5YKZxrdATyG1Q4SWTTSCeZ0Cbqz/jjzih0URQlAec159zs95JE4Qwhcn04UzOjbBZKZH+fekKbKpwm4BztUusmNZzZxzu+qgUFqgk47WMzSVGv0VxRqdvVHeupwjnfPjuOAwcSBzrgzAewTSicMr/wQgSAZlA4HUBaNZxVtUVZ8hpOTJEFMVbhBBB6q1jFEc5iB3H7VEMZUs0x9tuWUn5ESrklpXyj/vcTAN4I4DcAvElKuVP3TjbJkQk455goeu5iU2rNDaOxlFoAuPhywOtkTWkmQQjE5MJHiBcOeqrei5yJVtpMYDnkqmfXcI4IuhOXMjOx7e9joFNqK1/5Nxb3YtkUzuz3Z5uILJPCOYljbst1cE1uYFeM7jlmMAGnV+Nni/XEbp5+vpMiQVDTaRNwqmPbtd47dmZJqdXn0cFzQHe3tJ9bklKbqJkmpTYaTqm1b/K56yO5AVo0QHeQtphInKRrvJZe3mrjJ+md6MFH1xkdCCUK51ANpz6njEstomxQunIa0MHjNPhrWwCAg51reHZXKZwbdIDnw3Zh6r8oaWguhZv0ZN2N2+niQAOYwCKOI1XDuYiU2iKX2pLvIBaTK5xme3E0AHaeAEC4RmeG2i5NiinpUQrncD0wkGYw2Apngr7+JFk1SVuUkj6cxvArd51d8R0MtL8kzemyvis2sEOpV0by3dZsGlRl0CarquF0fXgIcdDTGR0jeuoWnctVIYuuySSmDzidABT2sGoSe+a9ttRcw+l4FSmc/oq69re3xj5VeOMDzsjtoANdw3nCDIOACVxqi5BS3oBKsz1xmIBznhpO22TgpkipBYCHvwm49x3ZPo8TEjs+vEGIGwcD1UIhmuwiYxTc/E3drtscqXAmfTjTtigDR90Iq174N8dAtDQBp5405E2DFu1SO4JJFc4/1f8buHTqPP70mO1t6ZTaOhVOJApnMym1QldH6TcFkE5IAUC6U3vUpqu2v/6jypDoga8e+VTfFVgNXJxdzannkAUK5+iAU2gVtds9wmpLfXfUQMB5aauNj/1xB9+8/g/Q2biA9454npmYDaXd6nGmaIRL7dt+MEkNnobW6mkAQHf3Op7tqYBiEwd4utdKWrTYiJKUWrsn7K5cwYUGbw+J0h9HiOJYtUVpNKXWKazhLFc4zXk0wf0oMUWKVMC5dhEDOLM7AevjKYpUqyM76EhqOJM2Jurx0LO+TxNwmqwaN6twFk20z+ho4XQne5/qBG6SUjtvH+l/uv4hPH1jHx/XvzfRh1OSQCyrTKklQM6v4onOGZymx3E4QuE0YkUzNZw59X/agHP9IiAj3O7vAWGVNZw1BZxVKZytDeD/+C1g/dL495wgpTb217BKT6GDHsTabC3ZlpkGbznHg56jLtquN0dwQIRQFqSPNUTjbVEAFWhu3T7TS2Phw8cALxz00XLlxDcfo2QONaq2PveooHu4D+cB9uIArqBMn8YqSHqqLUtKrVkUsPq4AUvQh3MEk6itgSvwHLYQTRBYpSm1NX42tznTIKVwxqlpkBlXd86A05yHT/w34MXvBM7eM/KpgevgF7/9DfiKV+obr61wmlOwoA/nkMKpU/+6R4fpg3E2VbgOLm2uYOdogM/0t0rV4JFtUcx4x0bhjLPXsfbmTPU4rQ31mv7+dTy728Xta4SABrgedcoVziLTIGvxc1s2q3Am/UGjCFEMdHDUuMJpjxlNoHAmCySTOM2b4MDUcG5cRhTLmV1qE1O7cAAhw2zAmZRCmPtfkcKpjsdwlEttwXX97vNr+NW/9qV44PJm5vEV30FoFM6StPpJ6LlrOHTT7YtjqHBW1dfT3biAs7SNQ61w5gNYY+Qzt7FNGYWLgM70n21DBUdX3et6E/Om1Na7EJEKQRV8t1u3q1ZIY7DNREd5O0hfpdSeF9ugE6hwcsCZo+eYGs75Joqm5mLe7cxC4y61cyKFDx8hjgZ6cjrhxHKUwunrld+254x01DPqT+pSe4AXBj4ub7UrV76MmrqsCqdTEFwuk8KZOuaOfo5RtScJkE3A6ddZw9lkSi05ENoaA0Bq2GPfBL0ZUuHs8/B1f2ns08+ttdJzJ2MapJ+QrKbb6Vs5owy9n/2uFXDKBgLOLTWRfnrnaIyz6CiFUx1TIlZqhYOokkl0Z0MpnNHhDTy/18Mda2qBbAed4rYoJnOjaKJmTXJUSu3cuzcxiStkPFAKJx012hZFgjJ1kEPtIIpek6TUTjCO+vuOolApnBuXEcZy9utnonAq5/ailNp8H+WilNrknjPkUls8+Jc2hwPK1cBFKPV7zXIdsXAEZc3aalayAK1wVhi0JcHrnNsUaxdwjrZV3S+GxYmkXrzJPpzqjWcIOC8DAG4Xz+tNVGQaVNOimOtWpHBOgePpRSC4oz+Xv4ZVOsIZbANrHHCeePquumi78wac06yOVoyTpNQ2/96zIB0fPqlVvsCZX+EkIgSuGN2DE6n6E1sK57W+i9tPj++nNC2Jwjmn4UJlmPqBZHVz2CwiURWXQeEc0ZDcZpSBVBFbnfoVTuNIN08/38nfTECQxEaQrZ8k+9pT4jBbtl0AwNU3AJcenPK1hAgCDkVWwGlUJT05hxg6eR1fTXj73aN0Uw3VcAJALMuP+UThzE+ohErZFLbCWcEkOtAptfHhDaVwdlRAuyM7haZBjjMiIEa29cSNhms4UwUwQhwNEGCQ6XtdN0rhHDarKm3xkXfwLMN8t+EgCTjjOQLOxGNA9+G0FxBMbbBpo2HeYqADzhAiUVwS3wA3r3BOPvYrgYu+Vjgdv4qA01KazaJYrQpnxW1RZm0dkmf1PDxE2KI9vbn8RKYkPb4qRMExTmL6uiIdcF4iFXA6VZkG1exSW6V78fj3NEZeJXOC1irOYhs+whNZw8kBZ44nOi/Bb8X3wJ0zWIswxc2qYkwAcWwUTsdTJxigJqcTToTSIGP4+YErRrZEAaz6iCgGpITs7+PZIxdXTs8wMR9D4oi2NCm1I2o4i1xql+AQmqQn6KgWOUWst1w4gmY29JgIrQQ04VJtUmo3TO6qMQ2yFs1mUiY2bgU2bwPe9F0z7VcMAQcxkjLq3ESt0ClTT2j7vSKFs8aA01J2yhYtUjfH4WvLgLxswFnFRLG9CQCQR9t4dreHy4EyDhqpcJpApeC9paVw7sl2o4tJIilhiOAODtSDDdZwxpQ3DRpvCJT06pxk0dhki3zhE0DUB87dhzCOZw44pXacpe72UE9X48RtxtoEzQNXfZ8DpJk0SRmHN76GcxRtz0lcas2C0Kw4gjIZRM2YBlXtUmuuAXNuc/UcAOAcbgAoKL8y9eINuNRmUmpnUThbG0Cwjgvxc8Pbm4XzL9VGlNXPxwBAaNOgSq7RE2J6hYclAacI1uCQ6mV6EgPO5h1tlpxPn34Mf/2zL8Kn5zxh0jz/RdRwqp+NmgbNgXSCbMA54XeWBBkFF/7Ac9AaYRgEWJOIOATCLkjGeCH0a1E4k56fy6Jw5lxqiwK6ZXKpnbSGc9xzDESErRWv1j6cxs1RjHCjqxKTUrseENBHodkJzTJRXD0L/MXfm3m/oiTgzKWg6Z8RHORvvW6gFc5eswrnmdUAviPQj+JSo5eRLrVQgYCIqk2phRugiwA4uoGdowEu6IBzW3YK57tJqUBBWxQ7pXYPK4l5VhOkKbUhvHBfPdhgSm2c78VYpOzkMH+byIdBB3/Bb/6wmii+5D2IfuOTGTVvGgYbVxFLgr/9OfQRYZBROLM1nE6uhrNPHszZnmTVeCt4bq+Ls24AwnSphI6gJMj15gw4/+QDt2D7KO2z20jASVS5whlJKjrDpkMHFOdpG0Bas5mQBJz113BmyxxmaIsCABuXcebGMwAqCDjvfov6VxPeAhROV6fURmUBZ8vK+tALEieJ4xGRNIhJQ513op0cyItoi7II06B5cJRpEAD4Qk5Rw6lvuAWBwziFU1gpXuirFfcDtHDlTPUraonqsKQBZ1HPzaSGcwlSaidxqZ1G4QRUHWedCqdRFJtJqVUK53qicJrJdHrtEX49K8VlxHBUwJmYBuUUzoKFpfVVFYRc3961NhRlX18DQlBSx1mmcIqSVK+IPAg5AKRUBk4VZbcciDVEB0oFOeuWK5xOSVsUsz+R00YIF3eebS7gSxXOGF5oFM4mTYOcbErtBDViSX3bJE7zJgjcewJ45M8DXgvRHCm15K/gSXkGwfZnIGSUOd5ichBLSgIU8xb9QoVT/f+FnsBrfuAX8YfX9eLNlOeSUYTd1nwB51c+eBkffN3V5HcS45XmeamjhrOSQEUHnBfoBQAFCxtljtNVUdQbeZaUWgDYuIytgVI4m+g/PQ+uaYvSZA2nVjijEYZBAOC2rWsiK5wnn2lqwcqIyAEkai2GH8XbXnoBkZRYC47J8LoBfKgUukDEhZO5IpLFgSKF0xWZ9ih5kgmQDIG+WnE/lK1aaziXJuB0cgpnQUCXuNQukcJZllI77Xn7pnvPlS5IzItxc5ynvdKkqLYoWuEECo04nEUEnCTgIoLv6BShvMJZcJ6f2VQrvE88fyN9UEYIIeDWvPhxabONz187GHPMG4VzeN9D8uDEA9VCBqhssbHrrsE7UgH4aUddJ3dkZ0gdBlJloWj/jBFNVxvjNRpwJm1DQrihah3TdEptZnKZ1HCWXAOMwjnJ5NmYNQUbEA99AADmCjhdh/BZeQse2vksHORqOIWDGJT2T9Y/k4CT0oDTlHF8fidGGEt89sYA92L6iXYkPCAG/KDa60iSaVTrwrxAldqKJFHo8js12hTmHJmU2nwNpzmXGzANmjelFgA2boVAsQHSsuFqp/4mA85U4Ryd9eS2rV7XJ1DhPCYRSXPcfrqDS5vtuSfaiSPeAlJqbz/dwYfeeFfj7zsr5HjwSK28ejMonEWL1IHrlAYUZLvUaoXziFqJeUiVJArnnA5/lWEUzpzL4bIqnEQEQdUqnN/5ZS+uZN9G0emoSX2nXf3xNIzqw7mWMw2yzyO34oniJETjFM6CpDQTqD91LQ04hYwQwan9ZmUcOktrOBMX3uGLTmwCzorbuPTcdWyQukZtYB8ShD2s4HRhDadK9yucSOmAcw8r6PgOzq83twBm9+H0I12f27RpkBV0kCiYaOfR59FE6YF6ewcv+wDWtHIbztEWJXAF/qe8BY/u/hIceSpj+CTJHRFwqvfNBJx6cfELO2oR5Avb6ticNk1TCheIgWBOhTNPkoVRo7niuc0VCN3rshqomprQYB2hCHA2VotJQ4sfJn2/zj6cyRwgF3DO8p7aOAhAs4ZkM5AonPMnRk+OLq+JSxROb0VdE0Py4bY2m9irRuGAM8fXvupWfM3D8zdcTS7oS77SsxS4QZJS25LdiQvF3/HARQiiQjfer/2S27AajF+9llEI9JTC2eqs1+Lsm/RUWxaFM5dSm/bhTJ8iknn14gNOQBlDlQW/09RwNsHVl70B2194H+54+etrf69E4fRMreTwYtciAk5JKuBckTmTmJKUWrRPAQAOXngGcSzV8ReHhcFp1ZjFpjIlXSSqw/CtMxIenHCQmByVqmdTMPA3sIHPAwDW5D7Q2oDsisKsN4doqOdkuvNqn29EbdxxdrXcobVi7BpOP9LHQ4M1nB/13wV39TReoX+XBXXOeT6/9Tp85HOfwztbW2O3f+PUy/BT4ZfiDa/4szBJcYMonrmP8b0X1vFR91Y4URcX8Dxu0EuSv/3WyuvxqReA9+fWPoxpUN9qv2VqOD+zrRZ0P7cdAmIGZUePX9Cu9jpiMo0maj0zIy3PBcLqrh+SRDVBIBF6rTNwD5/Uv49yqa3x2mfKauyA/9G/DFy4f/ptbaTz5kV0Z5gGL0mpbXC+oANOr8Tp2dcBJ1bPzW9KtYRwwJmDiCoZ54gcRLJ8kswoyA0QGNOgcC9xZhzHPefXcM/54jqg97369vIXmxucjJKU2o2N8ROLWTizodSu286dqmX7UzNUw6mOeTu4LHKuXSRiTFmJUThrdZ6dhmAVm+/9kWbeSwecZQqn16o+VXwcSuGM0OlfV8da56z6Q1nAuXEJAHA6eh6P3zjE7ac7IK1w1s0kNZxp7d/w/sTChyMHiMOBWm6saBIdBxvYoAN4DiEI90DtTaweuYV9aR1hAs7h9zZu2dcGAe442+zxYCagcRTBi5p3qf148BZcWk3VuUkUzt3O7fjh8GvxrgmMf8JgC98ZfhN+JVD3kGd2uvjMc/t4630XZtpf3xU4e+WlwBegWshY58oT7XvxC9EpfCCncPZ0wBkWKJx/9EKItZaL/b4L+LMonOrYabWrPW5EAzWcKkW0woCzwjYrYfssMDLgrN+lFjkDKgDAq791tm1ZCqdYgHfJNHg6vbVWQ6Y8+vp7eqOkdl1nR7jrs103lp0lmZ2dPGJyGnXAOs6Q48PTAac/2AWaSCUwF3crpfbUVj3v6+gLjTFEWTi5tigAsNH2sNFOUz2WqQ8noBXOCVxql0WRbRKlcMZYNQpnIk+nN31vIQqncqlt968DK2es3mom4CyYlHhtDFqncYmu4dNP61QzGTXSoNuk1JYdZ6KkLUosPLgyRKgbuU/UTmMS2pvYwAHOrbVA3W2gtYmLG63itiik0v3KUmp3ZLvR+k0gTaklGVsptc2ZBhEhG6AX1a7lcHKmPGWY50Sxqlf+l598ArEE/tRDl0teVc4Dr3hV8n+776vI1bSb9w5FgAHcTMBpsmqeORR4zysuoWcqf6c9n/Sx016pNuBMjos6TWZmrUkcub2KUmqBrDHMqICzAdOgSgJ+K+C8cmZJ5jojSE2Dmk+phVviXG+yPk6gYRDAAWdtSDiqsTkzFvLSlFq3vwO061EaMyQmFhEO9ncAAGdPna71vZJAb9GYC591I/vXH3ot/swjV5Lfk8nMkhzCjqDygDNROG/igNPcx0ygaY2vV3Ht1SRE5MChGK3etcKJVWHACcDZug23iOv41NN76ulxswpnqapf0vQ9Fi5cOUAUmjYu1eyzaG+hQz3csiaAoxtAewu3bLYLp7yOIHXfKXhvk7a4J1caDziFdb0NYpNS21zA+S1vuANf9yVW1kuBk3OeaerYzTETSwkpJX76tx/Hq+84NZcJ3avuuwfbUONkK9b5/TLXaiklDqiD0Or3bALOLnx82f0XE/fsqRdw9D2jXXFKrdNASm3VAWdlKbUAnHX7upjbZm6BrhYS86wK3mPtYqqYLnlKre81bxqUzLvKWqUFVkrtCWRJppMnj5g44JwU4QbwtWmQ09ueOKV2LszKVhzixg1lUHLhbE0BpzZCaTKFrJRgXd3ErJYdV8500LFcjZdN4XQETeRSuywpwI2iU2pXzfAlAScl1yCqqYF2GVL34Qy6z2dvoMnKffGkRGxexlX3eqJwChk2ci29sN7CRtvDqc7oCUHSK29ESq2LEIOwr59bzSTa7ahU/KsrfWD3KaC9hdfedRovu3Vz6LmCgCP4GIjhxS2yTIMWlVIr4xBBdIgegqR3ZRO85xWX8aZ702MwdtU1mdzRdfWm3dYkta7mObEEfvPzL+CL1w/x3ofm84LwPQfbK1fUL7bjtNkvk8ig3zuKJXZoHT2Rnuuhp+45+7KNl9yyjstn9WLulBNto0CuVJxSm7ZFqTPgdCoO2qpLqQ02bwEAxJKGA87EXK3+gLOSANFxgXX1eWoNkivA85tvi5LMt8q8PII1dbyuX2pmnxpmuROtjzGcUjs5QiucAjGot9dMSq3lUruzu4vLAC6dP1vPe61dAL7uZ4HbX1vP9qflZV8DnLmrNKWtqFXKIhmrcJqAc0kC5EYhAYLEZnxd/d6xJtY66EsWPRokJlXD6R09D9ySmp6YiVXgjwjsNm7FBflxfPoplXmgUmrrXzF3HYGPf/j1mdTyPMIYeRRMkKVQ/YT7fZWtUVVdmr+mAs639H8B2H0SuPcd+Ob77yx8LhHhzw0+jJedfgBvyv9NT3j20cbVM80GnLZLbSs+wJFoY5EWas9eeBO+sf9X8N0bt418ziT9fw3mKbFWN9cCF29/6cW59zO4cC/wud/PHG95ZVNYwe7fCj6M82fP4kv0c//4/GN4/+/uIjh9K9ZaHq5cOAVcw9QBwdZqB7gBCL/a60gS6NTZr5iKFf9ZkSQqS6n1NlStXgwani2WZFNUBU2QWj4VG5eBnceX3izTM21RFuBSW5pS67WA9310NtOmYwBHRDUhyWnEWfEkINwAHiJcDHR/tiYUTnNBjGPs7+4gloRbz9WkcALA3W8BFtALsZDWOnDnl5Y+hcj8W44AzqFyhZOIELgiWf2/qdC1kuu9Z9XvG+nqaKIMuosIOF24iOEe5hVOAkDYWh2xTxuXEcgu9ravYedoAJJxY9fSc2utUqfqVqAmxmvt4XBJOj58RDjqGYWzmn1u6YDz9c/9JLB1Fbjvy0uf/z/pRTgMhhfPTMAp2hulPYrrwLFcaoP4CF1a7LXw0tlN/LrzIE6tlPTEE5MvYpnnXNvv4ed/72n8yZffgrY//3d87qqaeG52UsU6X1tqdu+p7SP8pxvncf62e5PnktfGJ+JX4L6LKlXvzgtnAExvlnLbWd0fsEQRngXj4F5r30YqUA/noMqUWlNqULg9HWi2/Pp0ISmM90FF37+p41xyhdMPTEpt8y61pSm1AHDHG4CVJTGYrBhWOGsiJqcRo4sTgeMjwAAX/S4wQDM1nHpsPvmF53GIJ/FSt4VOjRf248b5tRbOrS1JGxcYhbP8OWstF60a2tosO6aGs9N9WjnBWmpmkmWxgB6wkgRO0S4oHgybIJAY7eKqJy2X6Br+4OldCBk2onBOgjm+rp4tyA5wlMLZ1QFnVS61W6dVsB5E+8Brv39sKqogKjTPEnplfWWtxoW1ESQKp4zRjg/QFYsNOB++cgqf+r63lZqMvfOBi/BdgY2V8eqbWZj7B//lc+iFMb7xNVcq2U/nnAoe7zyfNoR3cqZB5vd///vPAADefn+qrDr6ovmSW1TAefclHXDOaBpUtQ9B0hblWJkGieqy1/R1sXCuqBfmbjtdXymOqd0UEzgxT8RxCTiTGs4G7ytCp3aPCzhPMDzDrglJTiNGFycCXcN50TtUAWcjKbVqbB6+fQMvjVrwd5ozsDgOfMMjt+Or5nBYrBrXKU+pBYB/+L4HcWlzSVTkJiEBQRLBwdMZp0AAqTK4iBpOcnARL6hf1qYJOFXt2yW6hv/zX/wP/PWjI9xW1lO3SRJXx4KUWseDhxDXjroAqutF53Z0gLh6AXj5nx77fEFUqMoZhXN9q/nVc5M62esPsBYeoruAFO884xytz6238PXj2muZbelN/fL/fh7vecUl3D2iXdfUnLlbv8H4lNpPP72LF51fyxhCeXrH7tMB58XTKnD1vSlTWIVXfs7OiOOq7Ym6U2orDICoyu3pzA858s2qbekyvHndj7aq9zhmAWfjvS4dv/IsgePEch8Vx5gz6ytoBzVeRE8S+mZzwVP9MJtJqVU3uq9+8Ba85JSEt7Ix5gU3F64jsN5anuP3dMfH6U75hfrB20/hwsaSOAE3SMvz4JKEu//kUMAZmRv/AhySJTk4TzrgnErhVAHnY7f0cc/5Ndx1po0z60uykFDSh7PdbsOjED/wL38DACDdivZ59ZxaMHjdX5posqIMtoYfjzoXEElC58Ld1ezXFJi+fL/+B3+MS9ETCDZPVp85u+b9295c4fe7ebs6d9ZS1VLkUmrtsX77/dnv9bbTK9hc8fDyW1XWEOlMh3svTnm/27iszsuKJ+hnb7mCCAKnL04W2M/E+iVg7ZbKNnfHuTWsl6RiT0UScI6YihtVrC5MwFmVq+yFl6kAuVOTH0ZFCK2oN6pwAvo8Wp6F/KZhhbMmTq22gd7Nu5IxFdq167xQrpTN9OE0NZyRMuJYr+6GxFTPP33/w/BdXh8r4uq5NWDHBW0/PlSbmyicCwg4Y3Lgk+pJWRxwjrjZd84AToCvvofw1W/9EuCn2sDukqQhmQl3wSTwwtY6wjbhqzpPAdcB97aHqnnP1jrw4U8DrcmChK945SW87u7hCd/q5fvw8v4/xk+9+OFq9msKPK2ova/9azgb7uDsWz/U+D7UiVEZ/9SDl3GlSkMmxwX+wiczafJuLqXWVmrzRkWvufMM/sf3vCWtxdfXgalr9l79rcBDH5h278dy/o4HgO/4Y1yssyfrO/8eSjTEqVkJvOoclt0APW8DpJ2th6g6HXho+zrgrMo06NaHgb/6BXXNWmaEQCRH9Cuuk2/5FU6pZWpAuMvTxHDZ0av258S2+r3BPpyIQ2D7ceDux+p/T2ZmNqtaUT6BCOEAR9tA1EvUweRvjoNB5MNbwLUos3qc7ytWpnASabfDJ/SGouVxPUwUzoJ9d3y4MsTXnH8ScXgrHrz/pdW97xRZH3/z3cXve/f5NfzK97x7IeeSq1Mnr4SfBy6+HLgj76F7vLn34hrecM9ZfNtjNajHuXZaSQ1nLvC842wH95wfrvfLGL+ZlgzTXg+EU5/pXZ3BJlDuCjoLFQeBweZF1e5o1HvVeO2mKtuiGJY92NRI4eLSVrNu3UtjHLkgOCKqC+FUXu9wYtEpta86rdoJNNqHM+wC+88MTdQZ5thAQgWbwFC6zsZKC16wmJuc51pGI0FuEjKuHmzzVrUQBKhFoWW5lpak1MLx1Tj88a9D3PbI0jg82yxs4cb+vh79cPO1UzVzcaONn/jAq3Bxo/7aVEHZlGnfFRAEvOP+i+OPOaFNS5a8xm6pIVHt8bt6bvT2Ku8hmt++rkm/CY8H1/VxYbPhgPMmZ0nu4icQ4dZa7H2i0KuuF5wd1b6hiaJqMwEyk9qbOK+eOebYk4X8cSychfTgBIBLp1eBHRRPqMYFnBuXgT/6z+r/yxRwmvYFRdd2x9cLWF3g9kea3a1lx3xfp+8C7n3nYvflmOM62RZRq4GLf/HNj+CByxPWZbotnpvMQ9VprqvnR2+v5pRa31eLgi1/efwaGkO4vPDSMMtyFz953PkmdXNlxmMCzP3nm1E3ASvg/KL6yQEnc1yxJ495pZ4cYEGtYoxRzFD9JqAC0LI02Y1bVebBwTXgqd8BXvT2WvZxalobwN1vBS4X1EHatTm3ccCZwW0Bd70FePiDy5MefUw51fGx1ckq1a+6OoXz8Eu+HLjyump36mbijjdmTJzm5p63ja6xJ6o1KHrxg2/EzhOP4Pylq7W9x9Jy37v4PGgYDjjr4uFvWvQeHB/MRG3/2WbqN4F0kn7jC+onp9QyxxXbibZzJvs34aR1W01TGnBOoHACwC98H9DbBR7589Xv3yw4LvB1P1P8N1Mr1toEzryosV06FggBfP3PLnovTgTvf80VfMUrL82+gXf9cHU7czPyym+odnv3f5X6V4RwalWj/Yv3wf9z/6G27S817/6RRe/BTQfryczisQPOJhxqgXSye0MrnOtz3MAZZpGYgHPjckHqqgN4C2oVY5SseQLOT/4z4M43AxdfVv3+VY25jt32CBvGMbXR8hycW7v52j/dlNTtUsswDcJHMrN4jDIwOGw+pTY8AjrnFjcpZ5h5MUFmUVq4cFVd9CKYK+A0GQdSmcwcB5KA89WL3Q+GYU4GHHAyJwg+kpnFY6f8NaVwlhmtMMxxwgR2hQHn4kyDklSwfEsUQLt4l6SKmYyDy68Cbn9t9ftWB6YWnes3GYapAnI4W4I5MXANJ7N4bLONxmo4dTG+jDngZI43SUptQR3ym76r/j53oyir4Xzr95ebqnkt4Mv+DnD7a45PC4173gY89r3A5YcWvScMw5wE/sT3A6fuWPReMEwlcMDJLB67MXNTKbWAmhBHfTYMYo43ZQHni97W7L7YlKXUjjLJsHnVn612f+pm9Rzwur+06L1gGOak8NKvXPQeMExlsFbPLJ5FpNQCacofK5zMcWZZj2NRklLLMAzDMMxNAweczOJxrKbDTaXUAumEeJMVTuYYY7vULhNlNZwMwzAMw9w0cMDJLB7XUjibTKldVmWIYaYhWFM9OJettU9rQzVIdxfUB5RhGIZhmKWAaziZxbOolNrE3ZMVTuYY8+D7gbvevHytfR79MPDKP7PovWAYhmEYZsFwwMksnoWZBjlKGVo53dx7MkzVBKvAuRcvei+GaW81myLPMAzDMMxSwim1zOJZRFsUQKXUblw+Pm0XGIZhGIZhGOaYwQEns3gyKbUbzb2vcLh+k2EYhmEYhmFqhFNqmcUjhOqJ6bayjrV1c/ZFwOVXNfd+DMMwDMMwDHOTwQEnsxw4frOGQQDwvo82+34MwzAMwzAMc5PBKbXMcuD4bDDCMAzDMAzDMCcMDjiZ5cANmnWoZRiGYRiGYRimdjjgZJYDx2/WMIhhGIZhGIZhmNrhGk5mOXjoG4HTdy16LxiGYRiGYRiGqRAOOJnl4NG/vOg9YBiGYRiGYRimYjillmEYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWuCAk2EYhmEYhmEYhqkFDjgZhmEYhmEYhmGYWiApZb1vQPQ8gC/W+ibzcwbAtUXvBDMTPHbHGx6/4wuP3fGGx+/4wmN3vOHxO77w2JVzu5TybNEfag84jwNE9NtSyocWvR/M9PDYHW94/I4vPHbHGx6/4wuP3fGGx+/4wmM3O5xSyzAMwzAMwzAMw9QCB5wMwzAMwzAMwzBMLXDAqfhHi94BZmZ47I43PH7HFx674w2P3/GFx+54w+N3fOGxmxGu4WQYhmEYhmEYhmFqgRVOhmEYhmEYhmEYphY44GRuSojoJUT0KBE5i94XhmGY4wARPUREX7Lo/WAYhjlO8JyzooCTiDaI6N8T0ceJ6KNE5OvH/wkR/RoRfbf13PNE9CvW799HRJ/Q//6AiL5jxHt4RPRv9fY+YD3+YiL6uTH7t0lEv0xEv0pEb7cefwMR/eMxr71KRL+lX//KUY8t02un5SYcvw8C+F4AXw3gx6Z87VKN3004dj9n7fMzRPTIFK9dqrHT2z2x46ef93VE9Des3x8mot8hov9MRFdKXjf0vCZeOw034dj9TQDfDODb9P9HvW7px05v96YZPyJqW/v7CSK6QUS3jHjd0o/fSR47Inqrfs9fI6Jv0o9dJZ5zmt+P4/idmDnnXEgp5/4H4EMA3qL//xEA7wLwFQB+XD/2owDuBrAF4D8A+OSI7fwMgEsj/vZhAN+r//+vAKwBuBPAvwXwiTH7938DeD8AB8C/B0AAXg3gF80+lrz23wB4I4BVAP961GPL9Foev7Hf418D4Oj//95xHr+bbeysv3UA/EfoOvTjOHY3wfi9B8CvmffWj30SwF0AbgXwYyWvHXpeE6/lsSsdu+/SP1cB/PpxHrubcfysv10G8NPHefxO+Nj9JIAVAD6Az+nHeM55vMfvxMw55/lXicIppfxRKeXH9a9nATynP+RP68d+EcDrAERQEf5ufhtE9DCAJ6WUT454G3t7vwbgIQB7AL5ygl18PYCflVJGAD4L4AqAxwF80wSvvU9K+Qkp5b7aTXJHPAYieg8Rva/p187LzTZ+UsofBLBKRH8RwC9Yn+HYjd/NNnbW3z4E4CNSX1WP49gBJ378fhvAd1r7eQpAKKX8jJTycQDnrb99KxG9ZdTz6nrtPNxMYwcAUsq/RURnAXyPtU/Hcuz057mpxs/iOwD8gPnlOI7fSR47KeXXSykPoYKEff0wzzlzHKfxO0lzznmo9M1JpbdtSSl/g4j+LABzIOwCuEtKuaufV/TybwNg0j9+DsCG9befglI07O2dl1L+kr09ImpDrUbY/BDUBW8/99rfoMnSO7at/x8AODPisWeklB9dxGvHfYBJuYnG7xkAVwH8SQAfM388zuN3M42dvmi+E8CbzB+P89gBJ3P8pJSPE9Gd1kP2fgBAy3ruR8Y8r5bXVsFNMnaG+6EmYz9kPffYjh1wc40fEW0BuCql/B/Wc4/t+J3EsbP4WwD+rv7/tvU4zzkVx2n8gBM255yFygJOvZL1w0hXD/YBtPX/V1FSL0pEmwDOSSk/CwBSyncXPOcdens7yK78JEgpj6BWNfKv/S7r19J9KSAueG3RY8v02qm5ycYPUsrf0SuznwLw96d47dKN3802dgDeAuC/SCnj4ZeUvnbpxg440eOXx/5cALA+xfOaeO3U3ERjZ97rF4nozVCKwc8UPOXYjB1w840fgK8B8LMlfz8243eSx46I3gPgjJTyJ/RDPOfMvnYTx2v8TtScc1aqmvD6UNL1d0gpv6gf/u9QkjgAvAzAF0o28W4APz/mbabZXp7/RUQP6f8/AOCLZU/OsU1EF0gtidwJ4PkRjy3Ta6fiZhs/IvqveqU3ANCb5rUjHqv6tRNzs42dfvy9UDUZ0752qcYOOPHjl0FKeQPAaSIKiGgFgDfp85p47bTcTGNHRD4R/SYReVC1UHtFzzsuY2c+E26S8bP4KgD/etQfj8v4neSxI6IHAfxVAB+wHuY5Z5ZjNX4nac45D1UpnB8E8CCA7yK1MvARqIvar5ByQns7VMHtKP4EgL8z5j1+AsDPE9GjAO4D8JtT7N9HAPwTIvpNAPslOd9F/D8APgp1wP2SlHJAREOPAcmqxqqU8p81+doKuNnG728D+M8AjgAkK1nHdPxuqrHTj78KwP+0n3hMxw442eNXxP8LZWQAAOb7BhF9K4DPyLSup+h5lb92Tm6asZNS9onoHwL4DSil4NvN347p2AE30fgBABF1AGxIKV/IPX4cx+8kj92PQinBH1NxAt6NEfdCvu+Vskzjd5LmnLMja3QkgnKYei+ACxVt7xa9vY0ZXnsX1OpeMMNrXwbloiXKHlum1/L4lX+Pyz72PHY379idpPEbsb3XAnhsluc18Voeu3rG+DiMHY/f8R6/kzx2Tdy7+L5X3/jNM87HZfzG/SO9QwzDMAzDMAzDMAxTKQstIGUYhmEYhmEYhmFOLhxwMgzDMAzDMAzDMLXAASfDMAzDTAERvZyIXp577O8vZm8YhmEYZrnhGk6GYRiGmQIiej8ASCl/fLF7wjAMwzDLDwecDMMwDDMhRPQDAN6jf31SSvlm/fgnpJRv1P//7wCeA9AHcAHA/6f//TiADQAfk1L+QLN7zjAMwzCLgQNOhmEYhpmCIoUzF3B+GsDDAH4PwGMAvhvADoDfkVL+uO7v9mVSyuvN7jnDMAzDNA/XcDIMwzBMtTwrpdyHargdASAALwLwrUT0CQAdqB5xDMMwDHPicRe9AwzDMAxzzDgCcBoAiIjkZKlCfwjg56SUv0REXw/ghTp3kGEYhmGWBVY4GYZhGGY6Pg7gK4joVwE8OuFrfhDAt+vXvA3As3XtHMMwDMMsE1zDyTAMwzAMwzAMw9QCK5wMwzAMwzAMwzBMLXDAyTAMwzAMwzAMw9QCB5wMwzAMwzAMwzBMLXDAyTAMwzAMwzAMw9QCB5wMwzAMwzAMwzBMLXDAyTAMwzAMwzAMw9QCB5wMwzAMwzAMwzBMLfz/x5+Xeb/4ZtsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd_pre[0:365].plot(kind ='line', figsize=(16,8))\n",
    "plt.title('2017,01,01北京市关于pm2.5对于AQI数据的预测')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "3741a7a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_sequence(sequence, n_steps):\n",
    "\tX, y = list(), list()\n",
    "\tfor i in range(len(sequence)):\n",
    "\t\t# find the end of this pattern\n",
    "\t\tend_ix = i + n_steps\n",
    "\t\t# check if we are beyond the sequence\n",
    "\t\tif end_ix > len(sequence)-1:\n",
    "\t\t\tbreak\n",
    "\t\t# gather input and output parts of the pattern\n",
    "\t\tseq_x, seq_y = sequence[i:end_ix], sequence[end_ix]\n",
    "\t\tX.append(seq_x)\n",
    "\t\ty.append(seq_y)\n",
    "\treturn array(X), array(y)\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54716aeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "path_all2 = [r'D:\\污染\\2013',r'D:\\污染\\2014',r'D:\\污染\\2015',r'D:\\污染\\2016',r'D:\\污染\\2017',r'D:\\污染\\2018']\n",
    "pd_list = []\n",
    "for i in path_all2:\n",
    "    pd_list.append(get_pd(i))\n",
    "DataAll = pd.concat(pd_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9ed87b3a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9295fd5e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "49913886",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6db89b4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd9a1818",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0f1621e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
